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

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/infections-and-identified-cases-of-covid-19
Infections and Identified Cases of COVID-19 from Random Testing Data
2005.11277
https://arxiv.org/abs/2005.11277v1
https://arxiv.org/pdf/2005.11277v1.pdf
https://github.com/VasylHafych/COVID_Death_Delay_Analysis
false
false
true
none
https://paperswithcode.com/paper/relations-between-entanglement-bell
Relations between entanglement, Bell-inequality violation and teleportation fidelity for the two-qubit X states
1202.00157
https://arxiv.org/abs/1202.0157v1
https://arxiv.org/pdf/1202.0157v1.pdf
https://github.com/DuyenPay/PGN_Pascal
false
false
true
none
https://paperswithcode.com/paper/entity-embeddings-of-categorical-variables
Entity Embeddings of Categorical Variables
1604.06737
http://arxiv.org/abs/1604.06737v1
http://arxiv.org/pdf/1604.06737v1.pdf
https://github.com/btjones-me/fraud-pycaret-demonstration
false
false
true
none
https://paperswithcode.com/paper/a-neural-algorithm-of-artistic-style
A Neural Algorithm of Artistic Style
1508.06576
http://arxiv.org/abs/1508.06576v2
http://arxiv.org/pdf/1508.06576v2.pdf
https://github.com/tiijana/Neural-Style-Transfer-
false
false
true
tf
https://paperswithcode.com/paper/190600446
Generating Diverse High-Fidelity Images with VQ-VAE-2
1906.00446
https://arxiv.org/abs/1906.00446v1
https://arxiv.org/pdf/1906.00446v1.pdf
https://github.com/eric-yim/distribution_reconstruction
false
false
true
tf
https://paperswithcode.com/paper/objects-as-points
Objects as Points
1904.07850
http://arxiv.org/abs/1904.07850v2
http://arxiv.org/pdf/1904.07850v2.pdf
https://github.com/Khalifa-2020/centernet1
false
false
true
pytorch
https://paperswithcode.com/paper/on-the-impact-of-publicly-available-news-and
On the impact of publicly available news and information transfer to financial markets
2010.12002
https://arxiv.org/abs/2010.12002v1
https://arxiv.org/pdf/2010.12002v1.pdf
https://github.com/ffaltings/news_and_markets
false
false
true
none
https://paperswithcode.com/paper/automated-translating-beam-profiler-for-in
Automated translating beam profiler for in-situ laser beam spot-size and focal position measurements
1801.06508
https://arxiv.org/abs/1801.06508v1
https://arxiv.org/pdf/1801.06508v1.pdf
https://github.com/rainerkaufmann/BeamProfiler
false
false
true
none
https://paperswithcode.com/paper/autoencoding-beyond-pixels-using-a-learned
Autoencoding beyond pixels using a learned similarity metric
1512.09300
http://arxiv.org/abs/1512.09300v2
http://arxiv.org/pdf/1512.09300v2.pdf
https://github.com/baon6052/VAE-GAN_Pegasus
false
false
true
none
https://paperswithcode.com/paper/learning-in-cooperative-multiagent-systems
Learning in Cooperative Multiagent Systems Using Cognitive and Machine Models
2308.09219
https://arxiv.org/abs/2308.09219v1
https://arxiv.org/pdf/2308.09219v1.pdf
https://github.com/ddm-lab/greedy-hysteretic-lenient-maibl
true
true
false
none
https://paperswithcode.com/paper/singular-euler-maclaurin-expansion
Singular Euler-Maclaurin expansion
2003.12422
https://arxiv.org/abs/2003.12422v3
https://arxiv.org/pdf/2003.12422v3.pdf
https://github.com/andreasbuchheit/singular_euler_maclaurin
true
true
true
none
https://paperswithcode.com/paper/deep-learning-framework-from-scratch-using
Deep Learning Framework From Scratch Using Numpy
2011.08461
https://arxiv.org/abs/2011.08461v1
https://arxiv.org/pdf/2011.08461v1.pdf
https://github.com/a-nico/ArrayFlow
true
true
true
none
https://paperswithcode.com/paper/3d-human-motion-estimation-via-motion
3D Human Motion Estimation via Motion Compression and Refinement
2008.03789
https://arxiv.org/abs/2008.03789v2
https://arxiv.org/pdf/2008.03789v2.pdf
https://github.com/KlabCMU/MEVA
false
false
true
pytorch
https://paperswithcode.com/paper/adaptive-huber-regression
Adaptive Huber Regression
1706.06991
https://arxiv.org/abs/1706.06991v2
https://arxiv.org/pdf/1706.06991v2.pdf
https://github.com/fd0r/adaptative_huber_regression
false
false
true
none
https://paperswithcode.com/paper/free-view-synthesis
Free View Synthesis
2008.05511
https://arxiv.org/abs/2008.05511v1
https://arxiv.org/pdf/2008.05511v1.pdf
https://github.com/intel-isl/FreeViewSynthesis
true
false
false
pytorch
https://paperswithcode.com/paper/semantic-relation-classification-via-1
Semantic Relation Classification via Bidirectional LSTM Networks with Entity-aware Attention using Latent Entity Typing
1901.08163
http://arxiv.org/abs/1901.08163v1
http://arxiv.org/pdf/1901.08163v1.pdf
https://github.com/NEUNLP-RE/Entity-aware-RC
false
false
true
tf
https://paperswithcode.com/paper/hybridpose-6d-object-pose-estimation-under
HybridPose: 6D Object Pose Estimation under Hybrid Representations
2001.01869
https://arxiv.org/abs/2001.01869v4
https://arxiv.org/pdf/2001.01869v4.pdf
https://github.com/chronoshell/copyydscsv
false
false
true
pytorch
https://paperswithcode.com/paper/deep-residual-learning-for-image-recognition
Deep Residual Learning for Image Recognition
1512.03385
http://arxiv.org/abs/1512.03385v1
http://arxiv.org/pdf/1512.03385v1.pdf
https://github.com/MioChiu/ResNet_TensorFlow
false
false
true
tf
https://paperswithcode.com/paper/assessment-of-p-value-variability-in-the
Assessment of P-value variability in the current replicability crisis
1609.01664
https://arxiv.org/abs/1609.01664v3
https://arxiv.org/pdf/1609.01664v3.pdf
https://github.com/Saromen/Saromen
false
false
true
none
https://paperswithcode.com/paper/can-spatiotemporal-3d-cnns-retrace-the
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
1711.09577
http://arxiv.org/abs/1711.09577v2
http://arxiv.org/pdf/1711.09577v2.pdf
https://github.com/hjjpku/adaptive_sampler
false
false
true
pytorch
https://paperswithcode.com/paper/an-empirical-evaluation-of-generic
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
1803.01271
http://arxiv.org/abs/1803.01271v2
http://arxiv.org/pdf/1803.01271v2.pdf
https://github.com/anandharaju/Basic_TCN
false
false
true
tf
https://paperswithcode.com/paper/wavenet-a-generative-model-for-raw-audio
WaveNet: A Generative Model for Raw Audio
1609.03499
http://arxiv.org/abs/1609.03499v2
http://arxiv.org/pdf/1609.03499v2.pdf
https://github.com/anandharaju/Basic_TCN
false
false
true
tf
https://paperswithcode.com/paper/is-the-y-2175-a-strangeonium-hybrid-meson
Is the $Y(2175)$ a Strangeonium Hybrid Meson?
1905.12779
https://arxiv.org/abs/1905.12779v2
https://arxiv.org/pdf/1905.12779v2.pdf
https://github.com/hojasonn/GSR-Y2175
false
false
true
none
https://paperswithcode.com/paper/parallel-bayesian-optimization-of-multiple
Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement
2105.08195
https://arxiv.org/abs/2105.08195v2
https://arxiv.org/pdf/2105.08195v2.pdf
https://github.com/pytorch/botorch
true
true
false
pytorch
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/L706077/OCR-CRNN
false
false
true
pytorch
https://paperswithcode.com/paper/mmdetection-open-mmlab-detection-toolbox-and
MMDetection: Open MMLab Detection Toolbox and Benchmark
1906.07155
https://arxiv.org/abs/1906.07155v1
https://arxiv.org/pdf/1906.07155v1.pdf
https://github.com/tianhai123/mmdetection
false
false
true
pytorch
https://paperswithcode.com/paper/emissor-a-platform-for-capturing-multimodal
EMISSOR: A platform for capturing multimodal interactions as Episodic Memories and Interpretations with Situated Scenario-based Ontological References
2105.08388
https://arxiv.org/abs/2105.08388v1
https://arxiv.org/pdf/2105.08388v1.pdf
https://github.com/cltl/EMISSOR
true
true
false
none
https://paperswithcode.com/paper/covid-19-epidemic-in-mumbai-projections-full
COVID-19 Epidemic in Mumbai: Projections, full economic opening, and containment zones versus contact tracing and testing: An Update
2011.02032
https://arxiv.org/abs/2011.02032v1
https://arxiv.org/pdf/2011.02032v1.pdf
https://github.com/dasarpmar/epidemics-simulator-mumbai
true
true
false
none
https://paperswithcode.com/paper/discovering-physical-concepts-with-neural
Discovering physical concepts with neural networks
1807.10300
https://arxiv.org/abs/1807.10300v3
https://arxiv.org/pdf/1807.10300v3.pdf
https://github.com/reginareis/doutorado
false
false
true
tf
https://paperswithcode.com/paper/complexity-of-the-interpretability-logic-il
Complexity of the interpretability logic IL
1710.05599
https://arxiv.org/abs/1710.05599v4
https://arxiv.org/pdf/1710.05599v4.pdf
https://github.com/luka-mikec/provability_sat
false
false
true
none
https://paperswithcode.com/paper/you-only-look-once-unified-real-time-object
You Only Look Once: Unified, Real-Time Object Detection
1506.02640
http://arxiv.org/abs/1506.02640v5
http://arxiv.org/pdf/1506.02640v5.pdf
https://github.com/rudraina/Face-Verification-And-Validation
false
false
true
tf
https://paperswithcode.com/paper/yolo9000-better-faster-stronger
YOLO9000: Better, Faster, Stronger
1612.08242
http://arxiv.org/abs/1612.08242v1
http://arxiv.org/pdf/1612.08242v1.pdf
https://github.com/rudraina/Face-Verification-And-Validation
false
false
true
tf
https://paperswithcode.com/paper/adapt-vqe-is-insensitive-to-rough-parameter
ADAPT-VQE is insensitive to rough parameter landscapes and barren plateaus
2204.07179
https://arxiv.org/abs/2204.07179v1
https://arxiv.org/pdf/2204.07179v1.pdf
https://github.com/hrgrimsl/adapt
true
true
false
none
https://paperswithcode.com/paper/rater-an-r-package-for-fitting-statistical
Statistical Models for Repeated Categorical Ratings: The R Package rater
2010.09335
https://arxiv.org/abs/2010.09335v5
https://arxiv.org/pdf/2010.09335v5.pdf
https://github.com/jeffreypullin/rater
true
false
false
none
https://paperswithcode.com/paper/automatically-designing-cnn-architectures
Automatically designing CNN architectures using genetic algorithm for image classification
1808.03818
https://arxiv.org/abs/1808.03818v3
https://arxiv.org/pdf/1808.03818v3.pdf
https://github.com/shreyamohanty/2019-REU
false
false
true
none
https://paperswithcode.com/paper/when-llms-are-unfit-use-fastfit-fast-and
When LLMs are Unfit Use FastFit: Fast and Effective Text Classification with Many Classes
2404.12365
https://arxiv.org/abs/2404.12365v1
https://arxiv.org/pdf/2404.12365v1.pdf
https://github.com/ibm/fastfit
true
true
false
pytorch
https://paperswithcode.com/paper/multi-scale-attention-with-dense-encoder-for
Multi-Scale Attention with Dense Encoder for Handwritten Mathematical Expression Recognition
1801.03530
http://arxiv.org/abs/1801.03530v2
http://arxiv.org/pdf/1801.03530v2.pdf
https://github.com/learnpcclaimsapp/WAP-SAMPLE
false
false
true
none
https://paperswithcode.com/paper/image-inpainting-for-irregular-holes-using
Image Inpainting for Irregular Holes Using Partial Convolutions
1804.07723
http://arxiv.org/abs/1804.07723v2
http://arxiv.org/pdf/1804.07723v2.pdf
https://github.com/chefpr7/Image-Inpainting-using-Partial-Convolutional-Layers
false
false
true
tf
https://paperswithcode.com/paper/deeper-and-wider-siamese-networks-for-real
Deeper and Wider Siamese Networks for Real-Time Visual Tracking
1901.01660
http://arxiv.org/abs/1901.01660v3
http://arxiv.org/pdf/1901.01660v3.pdf
https://github.com/logiklesuraj/siamfcex
false
false
true
pytorch
https://paperswithcode.com/paper/siamrpn-evolution-of-siamese-visual-tracking
SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks
1812.11703
http://arxiv.org/abs/1812.11703v1
http://arxiv.org/pdf/1812.11703v1.pdf
https://github.com/logiklesuraj/siamfcex
false
false
true
pytorch
https://paperswithcode.com/paper/siamvgg-visual-tracking-using-deeper-siamese
SiamVGG: Visual Tracking using Deeper Siamese Networks
1902.02804
https://arxiv.org/abs/1902.02804v4
https://arxiv.org/pdf/1902.02804v4.pdf
https://github.com/logiklesuraj/siamfcex
false
false
true
pytorch
https://paperswithcode.com/paper/k-nearest-neighbor-optimization-via
k-Nearest Neighbor Optimization via Randomized Hyperstructure Convex Hull
1906.04559
https://arxiv.org/abs/1906.04559v1
https://arxiv.org/pdf/1906.04559v1.pdf
https://github.com/leeseojun17/ConvexHulledKNN
false
false
true
none
https://paperswithcode.com/paper/a-neural-algorithm-of-artistic-style
A Neural Algorithm of Artistic Style
1508.06576
http://arxiv.org/abs/1508.06576v2
http://arxiv.org/pdf/1508.06576v2.pdf
https://github.com/liuzhengwei127/Styfer
false
false
true
pytorch
https://paperswithcode.com/paper/addressing-issues-of-cross-linguality-in-open
Addressing Issues of Cross-Linguality in Open-Retrieval Question Answering Systems For Emergent Domains
2201.11153
https://arxiv.org/abs/2201.11153v1
https://arxiv.org/pdf/2201.11153v1.pdf
https://github.com/alon-albalak/xor-covid
true
true
true
pytorch
https://paperswithcode.com/paper/a-new-estimate-of-the-cutoff-value-in-the-bak
A New Estimate of the Cutoff Value in the Bak-Sneppen Model
2111.10473
https://arxiv.org/abs/2111.10473v3
https://arxiv.org/pdf/2111.10473v3.pdf
https://github.com/camafish/bak-sneppen
true
true
false
none
https://paperswithcode.com/paper/end-to-end-sequence-labeling-via-bi
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
1603.01354
http://arxiv.org/abs/1603.01354v5
http://arxiv.org/pdf/1603.01354v5.pdf
https://github.com/Akshayanti/supersense-sequence-labelling
false
false
true
none
https://paperswithcode.com/paper/connectionist-temporal-localization-for-sound
Connectionist Temporal Localization for Sound Event Detection with Sequential Labeling
1810.09052
http://arxiv.org/abs/1810.09052v3
http://arxiv.org/pdf/1810.09052v3.pdf
https://github.com/YashNita/Polyphonic-Sound-Event-Detection-with-Weak-Labeling-Dataset-given-
false
false
true
pytorch
https://paperswithcode.com/paper/hamiltonian-descent-methods
Hamiltonian Descent Methods
1809.05042
http://arxiv.org/abs/1809.05042v1
http://arxiv.org/pdf/1809.05042v1.pdf
https://github.com/mocchi-tam/Hamiltonian_Descent_Methods
false
false
true
none
https://paperswithcode.com/paper/learning-to-ask-neural-question-generation
Learning to Ask: Neural Question Generation for Reading Comprehension
1705.00106
http://arxiv.org/abs/1705.00106v1
http://arxiv.org/pdf/1705.00106v1.pdf
https://github.com/Prakhar0409/question-generation
false
false
true
pytorch
https://paperswithcode.com/paper/intraq-learning-synthetic-images-with-intra
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization
2111.09136
https://arxiv.org/abs/2111.09136v5
https://arxiv.org/pdf/2111.09136v5.pdf
https://github.com/zysxmu/intraq
true
true
true
pytorch
https://paperswithcode.com/paper/compressive-spectral-embedding-sidestepping
Compressive spectral embedding: sidestepping the SVD
1509.08360
http://arxiv.org/abs/1509.08360v1
http://arxiv.org/pdf/1509.08360v1.pdf
https://bitbucket.org/dineshkr/fastembed
true
true
false
none
https://paperswithcode.com/paper/processing-south-asian-languages-written-in-1
Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset
2007.01176
https://arxiv.org/abs/2007.01176v1
https://arxiv.org/pdf/2007.01176v1.pdf
https://github.com/google-research-datasets/dakshina
true
true
false
none
https://paperswithcode.com/paper/pyss3-a-python-package-implementing-a-novel
PySS3: A Python package implementing a novel text classifier with visualization tools for Explainable AI
1912.09322
https://arxiv.org/abs/1912.09322v2
https://arxiv.org/pdf/1912.09322v2.pdf
https://github.com/sergioburdisso/pyss3
true
true
true
none
https://paperswithcode.com/paper/learning-variational-word-masks-to-improve
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers
2010.00667
https://arxiv.org/abs/2010.00667v3
https://arxiv.org/pdf/2010.00667v3.pdf
https://github.com/UVa-NLP/VMASK
true
true
true
pytorch
https://paperswithcode.com/paper/for-self-supervised-learning-rationality-1
For self-supervised learning, Rationality implies generalization, provably
2010.08508
https://arxiv.org/abs/2010.08508v1
https://arxiv.org/pdf/2010.08508v1.pdf
https://github.com/ICLR2021-rep-gen/Rationality-Generalization
true
true
false
pytorch
https://paperswithcode.com/paper/hed-unet-combined-segmentation-and-edge
HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline
2103.01849
https://arxiv.org/abs/2103.01849v1
https://arxiv.org/pdf/2103.01849v1.pdf
https://github.com/2023-MindSpore-4/Code-5/tree/main/hed
false
false
false
mindspore
https://paperswithcode.com/paper/cointossx-an-open-source-low-latency-high
CoinTossX: An open-source low-latency high-throughput matching engine
2102.10925
https://arxiv.org/abs/2102.10925v1
https://arxiv.org/pdf/2102.10925v1.pdf
https://github.com/dharmeshsing/CoinTossX
true
true
false
none
https://paperswithcode.com/paper/mm-hand-3d-aware-multi-modal-guided-hand
MM-Hand: 3D-Aware Multi-Modal Guided Hand Generative Network for 3D Hand Pose Synthesis
2010.01158
https://arxiv.org/abs/2010.01158v1
https://arxiv.org/pdf/2010.01158v1.pdf
https://github.com/ScottHoang/mm-hand
true
true
false
pytorch
https://paperswithcode.com/paper/a-quantum-algorithm-for-finding-the-minimum
A Quantum Algorithm for Finding the Minimum
quant-ph/9607014
https://arxiv.org/abs/quant-ph/9607014v2
https://arxiv.org/pdf/quant-ph/9607014v2.pdf
https://github.com/Qiskit/qiskit-aqua
false
false
true
pytorch
https://paperswithcode.com/paper/materials-property-prediction-using-symmetry
Materials property prediction using symmetry-labeled graphs as atomic-position independent descriptors
1905.06048
https://arxiv.org/abs/1905.06048v3
https://arxiv.org/pdf/1905.06048v3.pdf
https://github.com/peterbjorgensen/vorosym
true
true
true
none
https://paperswithcode.com/paper/detecting-adversarial-attacks-on-neural
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight
1710.00814
http://arxiv.org/abs/1710.00814v1
http://arxiv.org/pdf/1710.00814v1.pdf
https://github.com/yenchenlin/rl-attack-detection
true
false
false
tf
https://paperswithcode.com/paper/textbrewer-an-open-source-knowledge
TextBrewer: An Open-Source Knowledge Distillation Toolkit for Natural Language Processing
2002.12620
https://arxiv.org/abs/2002.12620v2
https://arxiv.org/pdf/2002.12620v2.pdf
https://github.com/airaria/TextBrewer
true
false
true
pytorch
https://paperswithcode.com/paper/reviewviz-assisting-developers-perform
ReviewViz: Assisting Developers Perform Empirical Study on Energy Consumption Related Reviews for Mobile Applications
2009.06027
https://arxiv.org/abs/2009.06027v2
https://arxiv.org/pdf/2009.06027v2.pdf
https://github.com/Mohammad-Abdul-Hadi/Result-Set-Visualization-d3js-R
true
false
false
none
https://paperswithcode.com/paper/geo-spatial-data-visualization-and-critical
Geo-Spatial Data Visualization and Critical Metrics Predictions for Canadian Elections
2009.05936
https://arxiv.org/abs/2009.05936v1
https://arxiv.org/pdf/2009.05936v1.pdf
https://github.com/Mohammad-Abdul-Hadi/Canada-Map-R-Visualization-for-Election-Data
true
false
false
none
https://paperswithcode.com/paper/multistate-dynamical-processes-on-networks
Multistate dynamical processes on networks: Analysis through degree-based approximation frameworks
1709.09969
https://arxiv.org/abs/1709.09969v1
https://arxiv.org/pdf/1709.09969v1.pdf
https://github.com/peterfennell/multi-state-SOLVER
true
true
false
none
https://paperswithcode.com/paper/loss-aware-post-training-quantization
Loss Aware Post-training Quantization
1911.07190
https://arxiv.org/abs/1911.07190v2
https://arxiv.org/pdf/1911.07190v2.pdf
https://github.com/ynahshan/nn-quantization-pytorch/tree/master/lapq
true
false
false
pytorch
https://paperswithcode.com/paper/multicolumn-networks-for-face-recognition
Multicolumn Networks for Face Recognition
1807.09192
http://arxiv.org/abs/1807.09192v1
http://arxiv.org/pdf/1807.09192v1.pdf
https://github.com/ibendrup/MulticolumnNetwork
false
false
true
tf
https://paperswithcode.com/paper/large-scale-randomized-experiment-reveals
Large-scale randomized experiment reveals machine learning helps people learn and remember more effectively
2010.04430
https://arxiv.org/abs/2010.04430v1
https://arxiv.org/pdf/2010.04430v1.pdf
https://github.com/Networks-Learning/spaced-selection
true
true
true
none
https://paperswithcode.com/paper/scene-graph-modification-based-on-natural
Scene Graph Modification Based on Natural Language Commands
2010.02591
https://arxiv.org/abs/2010.02591v1
https://arxiv.org/pdf/2010.02591v1.pdf
https://github.com/xlhex/SceneGraphModification
true
true
true
pytorch
https://paperswithcode.com/paper/regularizing-neural-networks-via-adversarial
Regularizing Neural Networks via Adversarial Model Perturbation
2010.04925
https://arxiv.org/abs/2010.04925v4
https://arxiv.org/pdf/2010.04925v4.pdf
https://github.com/hiyouga/AMP-Regularizer
true
true
true
pytorch
https://paperswithcode.com/paper/bot-and-gender-detection-of-twitter-accounts
Bot and Gender Detection of Twitter Accounts Using Distortion and LSA
null
http://ceur-ws.org/Vol-2380/paper_210.pdf
http://ceur-ws.org/Vol-2380/paper_210.pdf
https://github.com/andreabac3/Bot-Gender-Profiling-Pan2019
true
false
false
none
https://paperswithcode.com/paper/algorithms-for-new-types-of-fair-stable
Algorithms for new types of fair stable matchings
2001.10875
https://arxiv.org/abs/2001.10875v5
https://arxiv.org/pdf/2001.10875v5.pdf
https://github.com/fmcooper/regret-equal-sm
false
false
true
none
https://paperswithcode.com/paper/grouped-heterogeneous-mixture-modeling-for
Grouped Heterogeneous Mixture Modeling for Clustered Data
1804.00888
https://arxiv.org/abs/1804.00888v2
https://arxiv.org/pdf/1804.00888v2.pdf
https://github.com/sshonosuke/GHM
true
true
true
none
https://paperswithcode.com/paper/discrete-event-simulation-of-quantum-walks
Discrete-event simulation of quantum walks
2005.03401
https://arxiv.org/abs/2005.03401v1
https://arxiv.org/pdf/2005.03401v1.pdf
https://jugit.fz-juelich.de/qip/quantum-walk
true
false
false
none
https://paperswithcode.com/paper/learning-an-adaptive-meta-model-generator-for
Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems
2111.04282
https://arxiv.org/abs/2111.04282v1
https://arxiv.org/pdf/2111.04282v1.pdf
https://github.com/danni9594/asmg
true
true
false
tf
https://paperswithcode.com/paper/length-adaptive-transformer-train-once-with-1
Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search
2010.07003
https://arxiv.org/abs/2010.07003v2
https://arxiv.org/pdf/2010.07003v2.pdf
https://github.com/clovaai/length-adaptive-transformer
true
true
true
pytorch
https://paperswithcode.com/paper/noise-assisted-variational-quantum
Noise-Assisted Variational Quantum Thermalization
2111.03935
https://arxiv.org/abs/2111.03935v1
https://arxiv.org/pdf/2111.03935v1.pdf
https://github.com/jfold/navqt
true
false
false
tf
https://paperswithcode.com/paper/learning-to-retrieve-how-to-train-a-dense
Learning To Retrieve: How to Train a Dense Retrieval Model Effectively and Efficiently
2010.10469
https://arxiv.org/abs/2010.10469v1
https://arxiv.org/pdf/2010.10469v1.pdf
https://github.com/jingtaozhan/RepBERT-Index
false
false
true
pytorch
https://paperswithcode.com/paper/fully-convolutional-siamese-networks-for-1
Fully-Convolutional Siamese Networks for Object Tracking
1606.09549
https://arxiv.org/abs/1606.09549v3
https://arxiv.org/pdf/1606.09549v3.pdf
https://github.com/logiklesuraj/siamfcex
false
false
true
pytorch
https://paperswithcode.com/paper/projective-isomorphisms-between-rational
Projective isomorphisms between rational surfaces
2010.08393
https://arxiv.org/abs/2010.08393v2
https://arxiv.org/pdf/2010.08393v2.pdf
https://github.com/niels-lubbes/surface_equivalence
true
true
false
none
https://paperswithcode.com/paper/non-parametric-inference-adaptive-to
Non-Parametric Inference Adaptive to Intrinsic Dimension
1901.03719
https://arxiv.org/abs/1901.03719v3
https://arxiv.org/pdf/1901.03719v3.pdf
https://github.com/khashayarkhv/np_inference_intrinsic
true
true
true
none
https://paperswithcode.com/paper/new-constraints-on-the-mass-bias-of-galaxy
New constraints on the mass bias of galaxy clusters from the power spectra of the thermal Sunyaev-Zeldovich effect and cosmic shear
1907.07870
https://arxiv.org/abs/1907.07870v2
https://arxiv.org/pdf/1907.07870v2.pdf
https://github.com/ryumakiya/pysz
false
false
true
none
https://paperswithcode.com/paper/machine-learning-based-index-modulation
Molecular Index Modulation using Convolutional Neural Networks
2103.09812
https://arxiv.org/abs/2103.09812v3
https://arxiv.org/pdf/2103.09812v3.pdf
https://github.com/nanonetworking/ml-index-modulation
false
false
true
none
https://paperswithcode.com/paper/lattice-strain-measurement-of-core-shell
Lattice strain measurement of core@shell electrocatalysts with 4D-STEM nanobeam electron diffraction
2001.01010
https://arxiv.org/abs/2001.01010v3
https://arxiv.org/pdf/2001.01010v3.pdf
https://github.com/dxm447/stemtool/tree/master/stemtool/nbed
true
false
false
none
https://paperswithcode.com/paper/bridging-the-gap-between-conversational
CR-Walker: Tree-Structured Graph Reasoning and Dialog Acts for Conversational Recommendation
2010.10333
https://arxiv.org/abs/2010.10333v2
https://arxiv.org/pdf/2010.10333v2.pdf
https://github.com/truthless11/CR-Walker
true
true
true
pytorch
https://paperswithcode.com/paper/non-stationary-gaussian-process-regression
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo
1508.04319
http://arxiv.org/abs/1508.04319v1
http://arxiv.org/pdf/1508.04319v1.pdf
https://github.com/markusheinonen/adaptivegp
true
true
false
none
https://paperswithcode.com/paper/online-timestamp-based-transactional
Online Timestamp-based Transactional Isolation Checking of Database Systems (Extended Version)
2504.01477
https://arxiv.org/abs/2504.01477v1
https://arxiv.org/pdf/2504.01477v1.pdf
https://github.com/fertilefragrance/timekiller
true
true
true
none
https://paperswithcode.com/paper/conjecturing-based-computational-discovery-of
Conjecturing-Based Discovery of Patterns in Data
2011.11576
https://arxiv.org/abs/2011.11576v4
https://arxiv.org/pdf/2011.11576v4.pdf
https://github.com/nvcleemp/conjecturing
true
true
false
none
https://paperswithcode.com/paper/evolutionary-planning-in-latent-space
Evolutionary Planning in Latent Space
2011.11293
https://arxiv.org/abs/2011.11293v1
https://arxiv.org/pdf/2011.11293v1.pdf
https://github.com/two2tee/WorldModelPlanning
true
true
true
pytorch
https://paperswithcode.com/paper/quo-vadis-action-recognition-a-new-model-and
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
1705.07750
http://arxiv.org/abs/1705.07750v3
http://arxiv.org/pdf/1705.07750v3.pdf
https://github.com/StanfordVL/RubiksNet
false
false
true
pytorch
https://paperswithcode.com/paper/liquid-warping-gan-with-attention-a-unified
Liquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis
2011.09055
https://arxiv.org/abs/2011.09055v2
https://arxiv.org/pdf/2011.09055v2.pdf
https://github.com/iPERDance/iPERCore
false
false
true
pytorch
https://paperswithcode.com/paper/motion-prediction-using-temporal-inception
Motion Prediction Using Temporal Inception Module
2010.03006
https://arxiv.org/abs/2010.03006v1
https://arxiv.org/pdf/2010.03006v1.pdf
https://github.com/tileb1/motion-prediction-tim
true
true
true
pytorch
https://paperswithcode.com/paper/efficient-neural-architecture-search-via-1
Efficient Neural Architecture Search via Parameter Sharing
1802.03268
http://arxiv.org/abs/1802.03268v2
http://arxiv.org/pdf/1802.03268v2.pdf
https://github.com/f51980280/ENAS-Implement
false
false
true
pytorch
https://paperswithcode.com/paper/polyloss-a-polynomial-expansion-perspective-1
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions
2204.12511
https://arxiv.org/abs/2204.12511v2
https://arxiv.org/pdf/2204.12511v2.pdf
https://github.com/jahongir7174/EfficientNetV2
false
false
false
pytorch
https://paperswithcode.com/paper/provable-defense-against-privacy-leakage-in
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective
2012.06043
https://arxiv.org/abs/2012.06043v1
https://arxiv.org/pdf/2012.06043v1.pdf
https://github.com/jeremy313/FLDRep
false
false
true
pytorch
https://paperswithcode.com/paper/object-detection-in-foggy-scenes-by-embedding
Object Detection in Foggy Scenes by Embedding Depth and Reconstruction into Domain Adaptation
2211.13409
https://arxiv.org/abs/2211.13409v1
https://arxiv.org/pdf/2211.13409v1.pdf
https://github.com/viml-cvdl/object-detection-in-foggy-scenes
true
true
false
pytorch
https://paperswithcode.com/paper/virtex-learning-visual-representations-from
VirTex: Learning Visual Representations from Textual Annotations
2006.06666
https://arxiv.org/abs/2006.06666v3
https://arxiv.org/pdf/2006.06666v3.pdf
https://github.com/rahulvigneswaran/longtail-buzz
false
false
true
none
https://paperswithcode.com/paper/190503375
Embarrassingly Shallow Autoencoders for Sparse Data
1905.03375
https://arxiv.org/abs/1905.03375v1
https://arxiv.org/pdf/1905.03375v1.pdf
https://github.com/AhmadRK94/NeuEASE
false
false
true
pytorch
https://paperswithcode.com/paper/pac-bayes-compression-bounds-so-tight-that
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization
2211.13609
https://arxiv.org/abs/2211.13609v1
https://arxiv.org/pdf/2211.13609v1.pdf
https://github.com/activatedgeek/tight-pac-bayes
true
true
false
pytorch
https://paperswithcode.com/paper/cstr-a-classification-perspective-on-scene
Revisiting Classification Perspective on Scene Text Recognition
2102.10884
https://arxiv.org/abs/2102.10884v3
https://arxiv.org/pdf/2102.10884v3.pdf
https://github.com/Media-Smart/vedastr
true
true
false
pytorch