Datasets:
pwc-archive
/
links-between-paper-and-code

Dataset card Data Studio Files
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https://paperswithcode.com/paper/edtc-a-corpus-for-discourse-level-topic-chain
EDTC: A Corpus for Discourse-Level Topic Chain Parsing
null
https://aclanthology.org/2021.findings-emnlp.113
https://aclanthology.org/2021.findings-emnlp.113.pdf
https://github.com/nlp-discourse-soochowu/dtcp
true
true
false
pytorch
https://paperswithcode.com/paper/writing-style-author-embedding-evaluation
Writing Style Author Embedding Evaluation
null
https://aclanthology.org/2021.eval4nlp-1.9
https://aclanthology.org/2021.eval4nlp-1.9.pdf
https://github.com/enzofleur/style_embedding_evaluation
true
true
false
none
https://paperswithcode.com/paper/countering-the-influence-of-essay-length-in
Countering the Influence of Essay Length in Neural Essay Scoring
null
https://aclanthology.org/2021.sustainlp-1.4
https://aclanthology.org/2021.sustainlp-1.4.pdf
https://github.com/sdeva14/sustai21-counter-neural-essay-length
true
true
false
pytorch
https://paperswithcode.com/paper/unsupervised-monocular-depth-estimation-with
Unsupervised Monocular Depth Estimation with Left-Right Consistency
1609.03677
http://arxiv.org/abs/1609.03677v3
http://arxiv.org/pdf/1609.03677v3.pdf
https://github.com/xown3197/3D_Pedestrian_Localization_2021ComputerVision
false
false
true
pytorch
https://paperswithcode.com/paper/unsupervised-monocular-depth-learning-in
Unsupervised Monocular Depth Learning in Dynamic Scenes
2010.16404
https://arxiv.org/abs/2010.16404v2
https://arxiv.org/pdf/2010.16404v2.pdf
https://github.com/CarloRadice/depth-and-motion-learning
false
false
true
tf
https://paperswithcode.com/paper/smells-in-system-user-interactive-tests
Smells in System User Interactive Tests
2111.02317
https://arxiv.org/abs/2111.02317v1
https://arxiv.org/pdf/2111.02317v1.pdf
https://github.com/kabinja/suit-smells-replication-package
true
true
false
none
https://paperswithcode.com/paper/improving-sequence-to-sequence-semantic
Improving Sequence-to-Sequence Semantic Parser for Task Oriented Dialog
null
https://aclanthology.org/2020.intexsempar-1.3
https://aclanthology.org/2020.intexsempar-1.3.pdf
https://github.com/cxuan2019/top
true
true
false
pytorch
https://paperswithcode.com/paper/offensive-language-detection-in-nepali-social
Offensive Language Detection in Nepali Social Media
null
https://aclanthology.org/2021.woah-1.7
https://aclanthology.org/2021.woah-1.7.pdf
https://github.com/nowalab/offensive-nepali
true
true
false
none
https://paperswithcode.com/paper/bert4rec-sequential-recommendation-with
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
1904.06690
https://arxiv.org/abs/1904.06690v2
https://arxiv.org/pdf/1904.06690v2.pdf
https://github.com/vatsalsaglani/bert4rec
false
false
false
pytorch
https://paperswithcode.com/paper/dual-attention-networks-for-multimodal
Dual Attention Networks for Multimodal Reasoning and Matching
1611.00471
http://arxiv.org/abs/1611.00471v2
http://arxiv.org/pdf/1611.00471v2.pdf
https://github.com/iammrhelo/pytorch-vqa-dan
false
false
true
pytorch
https://paperswithcode.com/paper/cnn-architectures-for-large-scale-audio
CNN Architectures for Large-Scale Audio Classification
1609.09430
http://arxiv.org/abs/1609.09430v2
http://arxiv.org/pdf/1609.09430v2.pdf
https://github.com/stanfordmlgroup/aihc-sum20-lung-sounds
false
false
true
pytorch
https://paperswithcode.com/paper/spread2rml-constructing-knowledge-graphs-by
Spread2RML: Constructing Knowledge Graphs by Predicting RML Mappings on Messy Spreadsheets
2110.12829
https://arxiv.org/abs/2110.12829v1
https://arxiv.org/pdf/2110.12829v1.pdf
https://github.com/mschroeder-github/spread2rml
true
false
false
none
https://paperswithcode.com/paper/polyhedral-mesh-quality-indicator-for-the
Polyhedral Mesh Quality Indicator for the Virtual Element Method
2112.11365
https://arxiv.org/abs/2112.11365v1
https://arxiv.org/pdf/2112.11365v1.pdf
https://github.com/tommasosorgente/vem-indicator-3d-dataset
true
true
false
none
https://paperswithcode.com/paper/on-the-fly-category-discovery
On-the-Fly Category Discovery
null
http://openaccess.thecvf.com//content/CVPR2023/html/Du_On-the-Fly_Category_Discovery_CVPR_2023_paper.html
http://openaccess.thecvf.com//content/CVPR2023/papers/Du_On-the-Fly_Category_Discovery_CVPR_2023_paper.pdf
https://github.com/pris-cv/on-the-fly-category-discovery
true
true
false
pytorch
https://paperswithcode.com/paper/a-graph-neural-network-based-approach-for
Identifying Possible Rumor Spreaders on Twitter: A Weak Supervised Learning Approach
2010.07647
https://arxiv.org/abs/2010.07647v2
https://arxiv.org/pdf/2010.07647v2.pdf
https://github.com/shakshi12/Rumor-Spreaders-using-GNN-approach-PHEME-dataset-
false
false
true
tf
https://paperswithcode.com/paper/non-intrusive-binaural-speech-intelligibility
Non-Intrusive Binaural Speech Intelligibility Prediction from Discrete Latent Representations
2111.12531
https://arxiv.org/abs/2111.12531v2
https://arxiv.org/pdf/2111.12531v2.pdf
https://github.com/vvvm23/stoi-vqcpc
true
true
true
pytorch
https://paperswithcode.com/paper/revisiting-graph-neural-networks-all-we-have
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
1905.09550
https://arxiv.org/abs/1905.09550v2
https://arxiv.org/pdf/1905.09550v2.pdf
https://github.com/hazdzz/gfNN
false
false
true
pytorch
https://paperswithcode.com/paper/mesoscopic-insights-orchestrating-multi-scale
Mesoscopic Insights: Orchestrating Multi-scale & Hybrid Architecture for Image Manipulation Localization
2412.13753
https://arxiv.org/abs/2412.13753v1
https://arxiv.org/pdf/2412.13753v1.pdf
https://github.com/scu-zjz/Mesorch
true
true
true
pytorch
https://paperswithcode.com/paper/multi-behavior-self-supervised-learning-for
Multi-behavior Self-supervised Learning for Recommendation
2305.18238
https://arxiv.org/abs/2305.18238v1
https://arxiv.org/pdf/2305.18238v1.pdf
https://github.com/scofield666/mbssl
true
true
false
pytorch
https://paperswithcode.com/paper/a-great-model-comparison-against-the
A GREAT model comparison against the cosmological constant
2111.13083
https://arxiv.org/abs/2111.13083v2
https://arxiv.org/pdf/2111.13083v2.pdf
https://github.com/snesseris/great-project
true
true
false
none
https://paperswithcode.com/paper/bert-pre-training-of-deep-bidirectional
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
1810.04805
https://arxiv.org/abs/1810.04805v2
https://arxiv.org/pdf/1810.04805v2.pdf
https://github.com/geondopark/ckd
false
false
true
pytorch
https://paperswithcode.com/paper/texttt-py-irt-a-scalable-item-response-theory
py-irt: A Scalable Item Response Theory Library for Python
2203.01282
https://arxiv.org/abs/2203.01282v2
https://arxiv.org/pdf/2203.01282v2.pdf
https://github.com/nd-ball/py-irt
true
true
false
pytorch
https://paperswithcode.com/paper/deep-predictive-coding-networks-for-video
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
1605.08104
http://arxiv.org/abs/1605.08104v5
http://arxiv.org/pdf/1605.08104v5.pdf
https://github.com/Mikkil5112/PredNet
false
false
true
tf
https://paperswithcode.com/paper/active-machine-learning-for-spatio-temporal
Enhanced spatio-temporal electric load forecasts using less data with active deep learning
2012.04407
https://arxiv.org/abs/2012.04407v2
https://arxiv.org/pdf/2012.04407v2.pdf
https://github.com/ArsamAryandoust/DataSelectionMaps
true
true
true
tf
https://paperswithcode.com/paper/video-action-classification-using-prednet
PredNet and Predictive Coding: A Critical Review
1906.11902
https://arxiv.org/abs/1906.11902v3
https://arxiv.org/pdf/1906.11902v3.pdf
https://github.com/Mikkil5112/PredNet
false
false
true
tf
https://paperswithcode.com/paper/an-end-to-end-trainable-neural-network-for
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
1507.05717
http://arxiv.org/abs/1507.05717v1
http://arxiv.org/pdf/1507.05717v1.pdf
https://github.com/chandan5362/Indian-Number-Plate-Recognition
false
false
true
none
https://paperswithcode.com/paper/discodisco-at-the-disrpt2021-shared-task-a
DisCoDisCo at the DISRPT2021 Shared Task: A System for Discourse Segmentation, Classification, and Connective Detection
2109.09777
https://arxiv.org/abs/2109.09777v1
https://arxiv.org/pdf/2109.09777v1.pdf
https://github.com/gucorpling/discodisco
true
true
true
pytorch
https://paperswithcode.com/paper/nafs-a-simple-yet-tough-to-beat-baseline-for-1
NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning
2206.08583
https://arxiv.org/abs/2206.08583v1
https://arxiv.org/pdf/2206.08583v1.pdf
https://github.com/zwt233/NAFS
true
false
false
pytorch
https://paperswithcode.com/paper/k-2-ie-kernel-method-based-kernel-intensity
K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes
2505.24704
https://arxiv.org/abs/2505.24704v1
https://arxiv.org/pdf/2505.24704v1.pdf
https://github.com/hidkim/k2ie
true
true
false
tf
https://paperswithcode.com/paper/multilingual-controllable-transformer-based
Multilingual Controllable Transformer-Based Lexical Simplification
2307.02120
https://arxiv.org/abs/2307.02120v1
https://arxiv.org/pdf/2307.02120v1.pdf
https://github.com/kimchengsheang/mtls
true
true
false
pytorch
https://paperswithcode.com/paper/strong-instance-segmentation-pipeline-for
Strong Instance Segmentation Pipeline for MMSports Challenge
2209.13899
https://arxiv.org/abs/2209.13899v1
https://arxiv.org/pdf/2209.13899v1.pdf
https://github.com/yjingyu/instanc_segmentation_pro
true
true
true
pytorch
https://paperswithcode.com/paper/a-decentralized-framework-for-kernel-pca-with
A Decentralized Framework for Kernel PCA with Projection Consensus Constraints
2211.15953
https://arxiv.org/abs/2211.15953v1
https://arxiv.org/pdf/2211.15953v1.pdf
https://github.com/yruikk/dkpca-admm
true
true
true
none
https://paperswithcode.com/paper/open-domain-hierarchical-event-schema
Open-Domain Hierarchical Event Schema Induction by Incremental Prompting and Verification
2307.01972
https://arxiv.org/abs/2307.01972v1
https://arxiv.org/pdf/2307.01972v1.pdf
https://github.com/raspberryice/inc-schema
true
true
false
none
https://paperswithcode.com/paper/reverse-image-filtering-using-total
Reverse image filtering using total derivative approximation and accelerated gradient descent
2112.04121
https://arxiv.org/abs/2112.04121v3
https://arxiv.org/pdf/2112.04121v3.pdf
https://github.com/fergaletto/ReverseFilter_TDA
true
false
true
none
https://paperswithcode.com/paper/mipi-2022-challenge-on-rgb-tof-depth
MIPI 2022 Challenge on RGB+ToF Depth Completion: Dataset and Report
2209.07057
https://arxiv.org/abs/2209.07057v1
https://arxiv.org/pdf/2209.07057v1.pdf
https://github.com/mipi-challenge/mipi2022
true
true
true
none
https://paperswithcode.com/paper/mipi-2022-challenge-on-rgbw-sensor-re-mosaic
MIPI 2022 Challenge on RGBW Sensor Re-mosaic: Dataset and Report
2209.08471
https://arxiv.org/abs/2209.08471v1
https://arxiv.org/pdf/2209.08471v1.pdf
https://github.com/mipi-challenge/mipi2022
true
true
true
none
https://paperswithcode.com/paper/mipi-2022-challenge-on-rgbw-sensor-fusion
MIPI 2022 Challenge on RGBW Sensor Fusion: Dataset and Report
2209.07530
https://arxiv.org/abs/2209.07530v2
https://arxiv.org/pdf/2209.07530v2.pdf
https://github.com/mipi-challenge/mipi2022
true
true
true
none
https://paperswithcode.com/paper/cmua-watermark-a-cross-model-universal
CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes
2105.10872
https://arxiv.org/abs/2105.10872v2
https://arxiv.org/pdf/2105.10872v2.pdf
https://github.com/vdigpku/cmua-watermark
true
true
true
pytorch
https://paperswithcode.com/paper/measuring-fairness-with-biased-rulers-a
Measuring Fairness with Biased Rulers: A Survey on Quantifying Biases in Pretrained Language Models
2112.07447
https://arxiv.org/abs/2112.07447v1
https://arxiv.org/pdf/2112.07447v1.pdf
https://github.com/ipieter/biased-rulers
true
true
false
pytorch
https://paperswithcode.com/paper/investigation-of-the-dead-time-duration-and
Dead time duration and active reset influence on the afterpulse probability of InGaAs/InP single-photon avalanche diodes
2104.03919
https://arxiv.org/abs/2104.03919v4
https://arxiv.org/pdf/2104.03919v4.pdf
https://github.com/akoziy98/Automated_Stand
false
false
true
none
https://paperswithcode.com/paper/emnist-an-extension-of-mnist-to-handwritten
EMNIST: an extension of MNIST to handwritten letters
1702.05373
http://arxiv.org/abs/1702.05373v2
http://arxiv.org/pdf/1702.05373v2.pdf
https://github.com/chuiyunjun/projectCSC413
false
false
true
none
https://paperswithcode.com/paper/a-variance-reduced-and-stabilized-proximal
A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization
2302.06790
https://arxiv.org/abs/2302.06790v1
https://arxiv.org/pdf/2302.06790v1.pdf
https://github.com/yutong-dai/s-pstorm
true
true
false
none
https://paperswithcode.com/paper/automatic-evaluation-and-moderation-of-open
Automatic Evaluation and Moderation of Open-domain Dialogue Systems
2111.02110
https://arxiv.org/abs/2111.02110v3
https://arxiv.org/pdf/2111.02110v3.pdf
https://github.com/lfdharo/DSTC10_Track5_Toxicity
true
true
false
pytorch
https://paperswithcode.com/paper/automated-grading-of-radiographic-knee
Knee arthritis severity measurement using deep learning: a publicly available algorithm with a multi-institutional validation showing radiologist-level performance
2203.08914
https://arxiv.org/abs/2203.08914v2
https://arxiv.org/pdf/2203.08914v2.pdf
https://github.com/maciejmazurowski/osteoarthritis-classification
true
true
true
pytorch
https://paperswithcode.com/paper/investigation-of-the-dependence-of-noise
Investigation of the dependence of noise characteristics of SPAD on the gate parameters in sine-wave gated single-photon detectors
2103.07363
https://arxiv.org/abs/2103.07363v3
https://arxiv.org/pdf/2103.07363v3.pdf
https://github.com/akoziy98/Automated_Stand
false
false
true
none
https://paperswithcode.com/paper/investigating-the-coherent-state-detection
Investigating the coherent state detection probability of InGaAs/InP SPAD-based single-photon detectors
2104.07952
https://arxiv.org/abs/2104.07952v1
https://arxiv.org/pdf/2104.07952v1.pdf
https://github.com/akoziy98/Automated_Stand
false
false
true
none
https://paperswithcode.com/paper/tensor-renormalization-of-three-dimensional
Tensor renormalization of three-dimensional Potts model
2201.01789
https://arxiv.org/abs/2201.01789v1
https://arxiv.org/pdf/2201.01789v1.pdf
https://github.com/rgjha/TensorCodes
true
true
false
pytorch
https://paperswithcode.com/paper/neural-discrete-representation-learning
Neural Discrete Representation Learning
1711.00937
http://arxiv.org/abs/1711.00937v2
http://arxiv.org/pdf/1711.00937v2.pdf
https://github.com/yhy258/VariationalAutoEncoders-Pytorch
false
false
true
pytorch
https://paperswithcode.com/paper/kaggledbqa-realistic-evaluation-of-text-to
KaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers
2106.11455
https://arxiv.org/abs/2106.11455v1
https://arxiv.org/pdf/2106.11455v1.pdf
https://github.com/chiahsuan156/KaggleDBQA
true
false
false
none
https://paperswithcode.com/paper/joint-entropy-search-for-maximally-informed
Joint Entropy Search for Maximally-Informed Bayesian Optimization
2206.04771
https://arxiv.org/abs/2206.04771v5
https://arxiv.org/pdf/2206.04771v5.pdf
https://github.com/jointentropysearch/jointentropysearch
true
true
false
none
https://paperswithcode.com/paper/signal-strength-and-noise-drive-feature-1
Signal Strength and Noise Drive Feature Preference in CNN Image Classifiers
2201.08893
https://arxiv.org/abs/2201.08893v1
https://arxiv.org/pdf/2201.08893v1.pdf
https://github.com/mwolff31/signal_preference
true
true
false
pytorch
https://paperswithcode.com/paper/a-parallel-corpus-of-python-functions-and
A parallel corpus of Python functions and documentation strings for automated code documentation and code generation
1707.02275
http://arxiv.org/abs/1707.02275v1
http://arxiv.org/pdf/1707.02275v1.pdf
https://github.com/ICSEG/M2TS
false
false
true
pytorch
https://paperswithcode.com/paper/recommendations-for-datasets-for-source-code
Recommendations for Datasets for Source Code Summarization
1904.02660
http://arxiv.org/abs/1904.02660v1
http://arxiv.org/pdf/1904.02660v1.pdf
https://github.com/ICSEG/M2TS
false
false
true
pytorch
https://paperswithcode.com/paper/squeeze-and-excitation-networks
Squeeze-and-Excitation Networks
1709.01507
https://arxiv.org/abs/1709.01507v4
https://arxiv.org/pdf/1709.01507v4.pdf
https://github.com/mehrdad-noori/brain-tumor-segmentation
false
false
true
tf
https://paperswithcode.com/paper/low-rank-constraints-for-fast-inference-in-1
Low-Rank Constraints for Fast Inference in Structured Models
2201.02715
https://arxiv.org/abs/2201.02715v1
https://arxiv.org/pdf/2201.02715v1.pdf
https://github.com/justinchiu/low-rank-models
true
true
false
pytorch
https://paperswithcode.com/paper/spikecv-open-a-continuous-computer-vision-era
SpikeCV: Open a Continuous Computer Vision Era
2303.11684
https://arxiv.org/abs/2303.11684v2
https://arxiv.org/pdf/2303.11684v2.pdf
https://github.com/zyj061/spikecv
true
true
false
pytorch
https://paperswithcode.com/paper/dissipativity-based-decentralized-co-design
Dissipativity-Based Decentralized Co-Design of Distributed Controllers and Communication Topologies for Vehicular Platoons
2312.06472
https://arxiv.org/abs/2312.06472v2
https://arxiv.org/pdf/2312.06472v2.pdf
https://github.com/ndzsong2/longitudinal-vehicular-platoon-simulator
true
true
false
none
https://paperswithcode.com/paper/online-multi-object-tracking-framework-with
Online Multi-Object Tracking Framework with the GMPHD Filter and Occlusion Group Management
1907.13347
https://arxiv.org/abs/1907.13347v1
https://arxiv.org/pdf/1907.13347v1.pdf
https://github.com/SonginCV/GMPHD-OGM_Tracker
true
false
true
none
https://paperswithcode.com/paper/boost-and-skip-a-simple-guidance-free
Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation
2502.06516
https://arxiv.org/abs/2502.06516v2
https://arxiv.org/pdf/2502.06516v2.pdf
https://github.com/soobin-um/bns
true
true
false
pytorch
https://paperswithcode.com/paper/projection-of-functionals-and-fast-pricing-of
Projection of Functionals and Fast Pricing of Exotic Options
2111.03713
https://arxiv.org/abs/2111.03713v3
https://arxiv.org/pdf/2111.03713v3.pdf
https://github.com/valentintissot/klmc
true
true
true
none
https://paperswithcode.com/paper/parallel-longest-common-subsequence-analysis
Parallel Longest Common SubSequence Analysis In Chapel
2309.09072
https://arxiv.org/abs/2309.09072v1
https://arxiv.org/pdf/2309.09072v1.pdf
https://github.com/soroushvahidi/parallel-longest-common-subsequence
true
true
false
none
https://paperswithcode.com/paper/sum-a-benchmark-dataset-of-semantic-urban
SUM: A Benchmark Dataset of Semantic Urban Meshes
2103.00355
https://arxiv.org/abs/2103.00355v2
https://arxiv.org/pdf/2103.00355v2.pdf
https://github.com/tudelft3d/SUMS-Semantic-Urban-Mesh-Segmentation-public
true
false
false
none
https://paperswithcode.com/paper/pvg-at-wassa-2021-a-multi-input-multi-task
PVG at WASSA 2021: A Multi-Input, Multi-Task, Transformer-Based Architecture for Empathy and Distress Prediction
2103.03296
https://arxiv.org/abs/2103.03296v1
https://arxiv.org/pdf/2103.03296v1.pdf
https://github.com/mr-atharva-kulkarni/EACL-WASSA-2021-Empathy-Distress
true
false
false
tf
https://paperswithcode.com/paper/cocon-a-data-set-on-combined-contextualized
CoCon: A Data Set on Combined Contextualized Research Artifact Use
2303.15193
https://arxiv.org/abs/2303.15193v1
https://arxiv.org/pdf/2303.15193v1.pdf
https://github.com/illdepence/contextgraph
true
true
false
pytorch
https://paperswithcode.com/paper/deep-generative-framework-for-interactive-3d
Deep Generative Framework for Interactive 3D Terrain Authoring and Manipulation
2201.02369
https://arxiv.org/abs/2201.02369v1
https://arxiv.org/pdf/2201.02369v1.pdf
https://github.com/Shanthika/TerrainAuthoring-Pytorch
true
false
true
pytorch
https://paperswithcode.com/paper/scaled-yolov4-scaling-cross-stage-partial
Scaled-YOLOv4: Scaling Cross Stage Partial Network
2011.08036
https://arxiv.org/abs/2011.08036v2
https://arxiv.org/pdf/2011.08036v2.pdf
https://github.com/xyuan-wyze/darknet
false
false
true
tf
https://paperswithcode.com/paper/cspnet-a-new-backbone-that-can-enhance
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
1911.11929
https://arxiv.org/abs/1911.11929v1
https://arxiv.org/pdf/1911.11929v1.pdf
https://github.com/xyuan-wyze/darknet
false
false
true
tf
https://paperswithcode.com/paper/yolov3-an-incremental-improvement
YOLOv3: An Incremental Improvement
1804.02767
http://arxiv.org/abs/1804.02767v1
http://arxiv.org/pdf/1804.02767v1.pdf
https://github.com/xyuan-wyze/darknet
false
false
true
tf
https://paperswithcode.com/paper/neural-ocr-post-hoc-correction-of-historical
Neural OCR Post-Hoc Correction of Historical Corpora
2102.00583
https://arxiv.org/abs/2102.00583v1
https://arxiv.org/pdf/2102.00583v1.pdf
https://github.com/GarfieldLyu/OCR_POST_DE
true
true
true
pytorch
https://paperswithcode.com/paper/yolov4-optimal-speed-and-accuracy-of-object
YOLOv4: Optimal Speed and Accuracy of Object Detection
2004.10934
https://arxiv.org/abs/2004.10934v1
https://arxiv.org/pdf/2004.10934v1.pdf
https://github.com/xyuan-wyze/darknet
false
false
true
tf
https://paperswithcode.com/paper/detect-influential-points-of-feature-rankings
Detect influential points of feature rankings
2303.10516
https://arxiv.org/abs/2303.10516v1
https://arxiv.org/pdf/2303.10516v1.pdf
https://github.com/shuostat/ips_on_feature_rankings
true
true
false
none
https://paperswithcode.com/paper/probing-pre-trained-language-models-for-cross
Probing Pre-Trained Language Models for Cross-Cultural Differences in Values
2203.13722
https://arxiv.org/abs/2203.13722v2
https://arxiv.org/pdf/2203.13722v2.pdf
https://github.com/copenlu/value-probing
true
true
false
none
https://paperswithcode.com/paper/deep-graph-neural-networks-with-shallow-1
Deep Graph Neural Networks with Shallow Subgraph Samplers
2012.01380
https://arxiv.org/abs/2012.01380v3
https://arxiv.org/pdf/2012.01380v3.pdf
https://github.com/facebookresearch/shaDow_GNN
true
false
true
pytorch
https://paperswithcode.com/paper/vector-based-data-improves-left-right-eye
Vector-Based Data Improves Left-Right Eye-Tracking Classifier Performance After a Covariate Distributional Shift
2208.00465
https://arxiv.org/abs/2208.00465v1
https://arxiv.org/pdf/2208.00465v1.pdf
https://github.com/brianxiang123/eegetcovariatedistributionalshift
true
true
false
none
https://paperswithcode.com/paper/a-state-distribution-matching-approach-to-non
A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning
2205.05212
https://arxiv.org/abs/2205.05212v1
https://arxiv.org/pdf/2205.05212v1.pdf
https://github.com/architsharma97/medal
true
false
false
pytorch
https://paperswithcode.com/paper/deep-learning-through-the-lens-of-example
Deep Learning Through the Lens of Example Difficulty
2106.09647
https://arxiv.org/abs/2106.09647v2
https://arxiv.org/pdf/2106.09647v2.pdf
https://github.com/pengbohua/AngularGap/tree/12dad1ec18d3c15a41835c3c342f82051d895ccc/standard_curriculum_learning/prediction_depth
false
false
false
pytorch
https://paperswithcode.com/paper/end-to-end-learning-for-self-driving-cars
End to End Learning for Self-Driving Cars
1604.07316
http://arxiv.org/abs/1604.07316v1
http://arxiv.org/pdf/1604.07316v1.pdf
https://github.com/drtupe/Behavioral_Cloning
false
false
true
tf
https://paperswithcode.com/paper/collective-explainable-ai-explaining
Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley Values
2110.01307
https://arxiv.org/abs/2110.01307v1
https://arxiv.org/pdf/2110.01307v1.pdf
https://github.com/fabien-couthouis/xai-in-rl
true
true
true
none
https://paperswithcode.com/paper/a-multi-agent-reinforcement-learning-model-of
A multi-agent reinforcement learning model of common-pool resource appropriation
1707.06600
http://arxiv.org/abs/1707.06600v2
http://arxiv.org/pdf/1707.06600v2.pdf
https://github.com/fabien-couthouis/xai-in-rl
false
false
true
none
https://paperswithcode.com/paper/msccl-microsoft-collective-communication
GC3: An Optimizing Compiler for GPU Collective Communication
2201.11840
https://arxiv.org/abs/2201.11840v3
https://arxiv.org/pdf/2201.11840v3.pdf
https://github.com/microsoft/msccl-tools
true
true
true
pytorch
https://paperswithcode.com/paper/llama-open-and-efficient-foundation-language-1
LLaMA: Open and Efficient Foundation Language Models
2302.13971
https://arxiv.org/abs/2302.13971v1
https://arxiv.org/pdf/2302.13971v1.pdf
https://github.com/xiaoman-zhang/PMC-VQA
false
false
true
pytorch
https://paperswithcode.com/paper/a-cooperation-graph-approach-for-multiagent
A Cooperation Graph Approach for Multiagent Sparse Reward Reinforcement Learning
2208.03002
https://arxiv.org/abs/2208.03002v1
https://arxiv.org/pdf/2208.03002v1.pdf
https://github.com/binary-husky/hmp2g
true
true
false
pytorch
https://paperswithcode.com/paper/metrics-quantization-and-registration-in
Metrics, quantization and registration in varifold spaces
1903.11196
https://arxiv.org/abs/1903.11196v1
https://arxiv.org/pdf/1903.11196v1.pdf
https://github.com/charoncode/Var_LDDMM
true
false
true
none
https://paperswithcode.com/paper/mastering-visual-continuous-control-improved
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
2107.09645
https://arxiv.org/abs/2107.09645v1
https://arxiv.org/pdf/2107.09645v1.pdf
https://github.com/architsharma97/medal
false
false
true
pytorch
https://paperswithcode.com/paper/generative-modeling-with-optimal-transport
Generative Modeling with Optimal Transport Maps
2110.02999
https://arxiv.org/abs/2110.02999v2
https://arxiv.org/pdf/2110.02999v2.pdf
https://github.com/LituRout/OptimalTransportModeling
true
false
false
pytorch
https://paperswithcode.com/paper/structural-temporal-graph-neural-networks-for
Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
2005.07427
https://arxiv.org/abs/2005.07427v2
https://arxiv.org/pdf/2005.07427v2.pdf
https://github.com/KnowledgeDiscovery/StrGNN
true
false
false
pytorch
https://paperswithcode.com/paper/predrnn-towards-a-resolution-of-the-deep-in
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
1804.06300
http://arxiv.org/abs/1804.06300v2
http://arxiv.org/pdf/1804.06300v2.pdf
https://github.com/mindspore-ai/models/tree/master/official/cv/predrnn%2B%2B
false
false
false
mindspore
https://paperswithcode.com/paper/comparison-of-spatio-temporal-models-for
Comparison of Spatio-Temporal Models for Human Motion and Pose Forecasting in Face-to-Face Interaction Scenarios
2203.03245
https://arxiv.org/abs/2203.03245v1
https://arxiv.org/pdf/2203.03245v1.pdf
https://github.com/crisie/udiva
true
true
false
none
https://paperswithcode.com/paper/dynamic-mlp-for-fine-grained-image
Dynamic MLP for Fine-Grained Image Classification by Leveraging Geographical and Temporal Information
2203.03253
https://arxiv.org/abs/2203.03253v1
https://arxiv.org/pdf/2203.03253v1.pdf
https://github.com/ylingfeng/dynamicmlp
true
true
true
pytorch
https://paperswithcode.com/paper/a-unified-framework-for-masked-and-mask-free
A Unified Framework for Masked and Mask-Free Face Recognition via Feature Rectification
2202.07358
https://arxiv.org/abs/2202.07358v1
https://arxiv.org/pdf/2202.07358v1.pdf
https://github.com/haoosz/ffr-net
true
true
true
pytorch
https://paperswithcode.com/paper/bashexplainer-retrieval-augmented-bash-code
BashExplainer: Retrieval-Augmented Bash Code Comment Generation based on Fine-tuned CodeBERT
2206.13325
https://arxiv.org/abs/2206.13325v1
https://arxiv.org/pdf/2206.13325v1.pdf
https://github.com/NTDXYG/BASHEXPLAINER
true
true
false
none
https://paperswithcode.com/paper/generative-invertible-quantum-neural-networks
Generative Invertible Quantum Neural Networks
2302.12906
https://arxiv.org/abs/2302.12906v3
https://arxiv.org/pdf/2302.12906v3.pdf
https://gitlab.com/RussellA/quantumML
true
true
false
pytorch
https://paperswithcode.com/paper/nedmp-neural-enhanced-dynamic-message-passing
NEDMP: Neural Enhanced Dynamic Message Passing
2202.06496
https://arxiv.org/abs/2202.06496v1
https://arxiv.org/pdf/2202.06496v1.pdf
https://github.com/feigsss/nedmp
true
true
false
pytorch
https://paperswithcode.com/paper/distributing-persistent-homology-via-spectral
Distributing Persistent Homology via Spectral Sequences
1907.05228
https://arxiv.org/abs/1907.05228v1
https://arxiv.org/pdf/1907.05228v1.pdf
https://github.com/atorras1618/PerMaViss
false
false
true
none
https://paperswithcode.com/paper/r-local-sensing-improved-algorithm-and
r-local sensing: Improved algorithm and applications
2110.14034
https://arxiv.org/abs/2110.14034v3
https://arxiv.org/pdf/2110.14034v3.pdf
https://github.com/aabbas02/proximal-alt-min-for-uls-udgp
true
true
true
none
https://paperswithcode.com/paper/communication-efficient-zeroth-order
Communication-Efficient Zeroth-Order Distributed Online Optimization: Algorithm, Theory, and Applications
2306.05655
https://arxiv.org/abs/2306.05655v1
https://arxiv.org/pdf/2306.05655v1.pdf
https://github.com/sunses-hub/fed-ef-zo-sgd
true
true
false
none
https://paperswithcode.com/paper/denoising-diffusion-probabilistic-models
Denoising Diffusion Probabilistic Models
2006.11239
https://arxiv.org/abs/2006.11239v2
https://arxiv.org/pdf/2006.11239v2.pdf
https://github.com/keonlee9420/DiffGAN-TTS
false
false
true
pytorch
https://paperswithcode.com/paper/tackling-the-generative-learning-trilemma-1
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
2112.07804
https://arxiv.org/abs/2112.07804v2
https://arxiv.org/pdf/2112.07804v2.pdf
https://github.com/keonlee9420/DiffGAN-TTS
false
false
true
pytorch
https://paperswithcode.com/paper/diffsinger-diffusion-acoustic-model-for
DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism
2105.02446
https://arxiv.org/abs/2105.02446v6
https://arxiv.org/pdf/2105.02446v6.pdf
https://github.com/keonlee9420/DiffGAN-TTS
false
false
true
pytorch
https://paperswithcode.com/paper/divide-and-conquer-text-semantic-matching-1
Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents
2203.02898
https://arxiv.org/abs/2203.02898v1
https://arxiv.org/pdf/2203.02898v1.pdf
https://github.com/rowitzou/dc-match
true
true
true
pytorch