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

Dataset card Data Studio Files
xet
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https://paperswithcode.com/paper/propmend-hypernetworks-for-knowledge
PropMEND: Hypernetworks for Knowledge Propagation in LLMs
2506.08920
https://arxiv.org/abs/2506.08920v1
https://arxiv.org/pdf/2506.08920v1.pdf
https://github.com/leo-liuzy/propmend
true
true
true
pytorch
https://paperswithcode.com/paper/efc-elastic-feature-consolidation-with
EFC++: Elastic Feature Consolidation with Prototype Re-balancing for Cold Start Exemplar-free Incremental Learning
2503.10439
https://arxiv.org/abs/2503.10439v1
https://arxiv.org/pdf/2503.10439v1.pdf
https://github.com/simomagi/elastic_feature_consolidation
false
false
true
pytorch
https://paperswithcode.com/paper/end-to-end-and-highly-efficient
End-to-End and Highly-Efficient Differentiable Simulation for Robotics
2409.07107
https://arxiv.org/abs/2409.07107v2
https://arxiv.org/pdf/2409.07107v2.pdf
https://github.com/simple-robotics/simple
true
false
false
none
https://paperswithcode.com/paper/doge-defensive-output-generation-for-llm
DOGe: Defensive Output Generation for LLM Protection Against Knowledge Distillation
2505.19504
https://arxiv.org/abs/2505.19504v1
https://arxiv.org/pdf/2505.19504v1.pdf
https://github.com/unites-lab/doge
true
true
false
pytorch
https://paperswithcode.com/paper/hunyuan3d-2-0-scaling-diffusion-models-for
Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation
2501.12202
https://arxiv.org/abs/2501.12202v2
https://arxiv.org/pdf/2501.12202v2.pdf
https://github.com/tencent/hunyuan3d-2
true
true
true
pytorch
https://paperswithcode.com/paper/hunyuan3d-2-5-towards-high-fidelity-3d-assets
Hunyuan3D 2.5: Towards High-Fidelity 3D Assets Generation with Ultimate Details
2506.16504
https://arxiv.org/abs/2506.16504v1
https://arxiv.org/pdf/2506.16504v1.pdf
https://github.com/tencent/hunyuan3d-2
true
true
true
pytorch
https://paperswithcode.com/paper/investigation-of-neoclassical-tearing-mode
Investigation of Neoclassical Tearing Mode Detection by ECE Radiometry in Tokamak Reactors via Asymptotic Matching Techniques
2506.05553
https://arxiv.org/abs/2506.05553v1
https://arxiv.org/pdf/2506.05553v1.pdf
https://github.com/rfitzp/TJ
true
true
false
none
https://paperswithcode.com/paper/alita-generalist-agent-enabling-scalable
Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution
2505.20286
https://arxiv.org/abs/2505.20286v1
https://arxiv.org/pdf/2505.20286v1.pdf
https://github.com/charlesq9/alita
true
true
true
none
https://paperswithcode.com/paper/autoregressive-semantic-visual-reconstruction
Autoregressive Semantic Visual Reconstruction Helps VLMs Understand Better
2506.09040
https://arxiv.org/abs/2506.09040v1
https://arxiv.org/pdf/2506.09040v1.pdf
https://github.com/alenjandrowang/asvr
true
true
true
pytorch
https://paperswithcode.com/paper/squwals-a-szegedy-quantum-walks-simulator
SQUWALS: A Szegedy QUantum WALks Simulator
2307.14314
https://arxiv.org/abs/2307.14314v1
https://arxiv.org/pdf/2307.14314v1.pdf
https://github.com/ortegasa/squwals-repo
true
true
true
none
https://paperswithcode.com/paper/into-the-unknown-applying-inductive-spatial
Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places
2506.14070
https://arxiv.org/abs/2506.14070v1
https://arxiv.org/pdf/2506.14070v1.pdf
https://github.com/xlwang233/into-the-unknown
true
true
true
pytorch
https://paperswithcode.com/paper/mxplainer-explain-and-learn-insights-by
Mxplainer: Explain and Learn Insights by Imitating Mahjong Agents
2506.14246
https://arxiv.org/abs/2506.14246v1
https://arxiv.org/pdf/2506.14246v1.pdf
https://github.com/lingfeng158/mxplainer
true
true
false
pytorch
https://paperswithcode.com/paper/lemore-learn-more-details-for-lightweight
LeMoRe: Learn More Details for Lightweight Semantic Segmentation
2505.23093
https://arxiv.org/abs/2505.23093v1
https://arxiv.org/pdf/2505.23093v1.pdf
https://github.com/miannaeem-lab/lemore
true
true
true
none
https://paperswithcode.com/paper/generating-exceptional-behavior-tests-with
exLong: Generating Exceptional Behavior Tests with Large Language Models
2405.14619
https://arxiv.org/abs/2405.14619v3
https://arxiv.org/pdf/2405.14619v3.pdf
https://github.com/engineeringsoftware/exlong
false
false
true
none
https://paperswithcode.com/paper/a-comprehensive-survey-of-deep-research
A Comprehensive Survey of Deep Research: Systems, Methodologies, and Applications
2506.12594
https://arxiv.org/abs/2506.12594v1
https://arxiv.org/pdf/2506.12594v1.pdf
https://github.com/scienceaix/deepresearch
true
true
true
none
https://paperswithcode.com/paper/cai-an-open-bug-bounty-ready-cybersecurity-ai
CAI: An Open, Bug Bounty-Ready Cybersecurity AI
2504.06017
https://arxiv.org/abs/2504.06017v2
https://arxiv.org/pdf/2504.06017v2.pdf
https://github.com/greydgl/pentestgpt
false
false
true
none
https://paperswithcode.com/paper/fdm-printing-a-fabrication-method-for-fluidic
FDM Printing: a Fabrication Method for Fluidic Soft Circuits?
2312.01131
https://arxiv.org/abs/2312.01131v1
https://arxiv.org/pdf/2312.01131v1.pdf
https://github.com/roboticmaterialsgroup/fluidlogic
false
false
true
none
https://paperswithcode.com/paper/clearervoice-studio-bridging-advanced-speech
ClearerVoice-Studio: Bridging Advanced Speech Processing Research and Practical Deployment
2506.19398
https://arxiv.org/abs/2506.19398v1
https://arxiv.org/pdf/2506.19398v1.pdf
https://github.com/modelscope/ClearerVoice-Studio
true
true
true
pytorch
https://paperswithcode.com/paper/bs-ldm-effective-bone-suppression-in-high
BS-LDM: Effective Bone Suppression in High-Resolution Chest X-Ray Images with Conditional Latent Diffusion Models
2412.15670
https://arxiv.org/abs/2412.15670v4
https://arxiv.org/pdf/2412.15670v4.pdf
https://github.com/diaoquesang/BS-LDM
true
true
true
pytorch
https://paperswithcode.com/paper/scene-graph-parsing-as-dependency-parsing
Scene Graph Parsing as Dependency Parsing
1803.09189
http://arxiv.org/abs/1803.09189v1
http://arxiv.org/pdf/1803.09189v1.pdf
https://github.com/zhuang-li/factual
false
false
true
pytorch
https://paperswithcode.com/paper/do-you-really-mean-that-content-driven-audio
Do You Really Mean That? Content Driven Audio-Visual Deepfake Dataset and Multimodal Method for Temporal Forgery Localization
2204.06228
https://arxiv.org/abs/2204.06228v2
https://arxiv.org/pdf/2204.06228v2.pdf
https://github.com/ControlNet/LAV-DF
true
false
true
pytorch
https://paperswithcode.com/paper/tensorf-tensorial-radiance-fields
TensoRF: Tensorial Radiance Fields
2203.09517
https://arxiv.org/abs/2203.09517v2
https://arxiv.org/pdf/2203.09517v2.pdf
https://github.com/apchenstu/TensoRF
true
false
true
pytorch
https://paperswithcode.com/paper/online-learning-of-long-range-dependencies
Online learning of long-range dependencies
2305.15947
https://arxiv.org/abs/2305.15947v2
https://arxiv.org/pdf/2305.15947v2.pdf
https://github.com/nicolaszucchet/minimal-lru
false
false
true
jax
https://paperswithcode.com/paper/autoadaptive-medical-segment-anything-model
Autoadaptive Medical Segment Anything Model
2507.01828
https://arxiv.org/abs/2507.01828v1
https://arxiv.org/pdf/2507.01828v1.pdf
https://github.com/tbwa233/ada-sam
true
true
false
none
https://paperswithcode.com/paper/remember-past-anticipate-future-learning
Remember Past, Anticipate Future: Learning Continual Multimodal Misinformation Detectors
2507.05939
https://arxiv.org/abs/2507.05939v1
https://arxiv.org/pdf/2507.05939v1.pdf
https://github.com/wangbing1416/daedcmd
true
true
false
pytorch
https://paperswithcode.com/paper/deepresearch-bench-a-comprehensive-benchmark
DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents
2506.11763
https://arxiv.org/abs/2506.11763v1
https://arxiv.org/pdf/2506.11763v1.pdf
https://github.com/ayanami0730/deep_research_bench
true
true
true
none
https://paperswithcode.com/paper/hashed-watermark-as-a-filter-defeating
Hashed Watermark as a Filter: Defeating Forging and Overwriting Attacks in Weight-based Neural Network Watermarking
2507.11137
https://arxiv.org/abs/2507.11137v1
https://arxiv.org/pdf/2507.11137v1.pdf
https://github.com/airesearch-group/neuralmark
true
true
true
pytorch
https://paperswithcode.com/paper/fully-automated-fact-checking-using-external
Fully Automated Fact Checking Using External Sources
1710.00341
http://arxiv.org/abs/1710.00341v1
http://arxiv.org/pdf/1710.00341v1.pdf
https://github.com/gkaradzhov/FactcheckingRANLP
true
true
true
none
https://paperswithcode.com/paper/deformable-convolutional-networks
Deformable Convolutional Networks
1703.06211
http://arxiv.org/abs/1703.06211v3
http://arxiv.org/pdf/1703.06211v3.pdf
https://github.com/qilei123/fpn_crop_v1_5d
false
false
true
mxnet
https://paperswithcode.com/paper/conic-scan-and-cover-algorithms-for
Conic Scan-and-Cover algorithms for nonparametric topic modeling
1710.02952
http://arxiv.org/abs/1710.02952v1
http://arxiv.org/pdf/1710.02952v1.pdf
https://github.com/moonfolk/Geometric-Topic-Modeling
true
true
false
none
https://paperswithcode.com/paper/sign-is-not-a-remedy-multiset-to-multiset
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
2405.20652
https://arxiv.org/abs/2405.20652v1
https://arxiv.org/pdf/2405.20652v1.pdf
https://github.com/Jinx-byebye/m2mgnn
true
true
false
pytorch
https://paperswithcode.com/paper/passgan-a-deep-learning-approach-for-password
PassGAN: A Deep Learning Approach for Password Guessing
1709.00440
http://arxiv.org/abs/1709.00440v3
http://arxiv.org/pdf/1709.00440v3.pdf
https://github.com/achen04/passwordcracking
false
false
true
none
https://paperswithcode.com/paper/compnet-complementary-segmentation-network
CompNet: Complementary Segmentation Network for Brain MRI Extraction
1804.00521
http://arxiv.org/abs/1804.00521v2
http://arxiv.org/pdf/1804.00521v2.pdf
https://github.com/SenthilCaesar/CNN-Brain-MRI-Segmentation
false
false
true
tf
https://paperswithcode.com/paper/the-greedy-and-recursive-search-for
The Greedy and Recursive Search for Morphological Productivity
2105.05790
https://arxiv.org/abs/2105.05790v1
https://arxiv.org/pdf/2105.05790v1.pdf
https://github.com/cbelth/ATP-morphology
true
true
false
none
https://paperswithcode.com/paper/relation-networks-for-object-detection
Relation Networks for Object Detection
1711.11575
http://arxiv.org/abs/1711.11575v2
http://arxiv.org/pdf/1711.11575v2.pdf
https://github.com/insigh/Relation_Network_for_Objection
false
false
true
mxnet
https://paperswithcode.com/paper/understanding-multimodal-contrastive-learning
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data
2302.06232
https://arxiv.org/abs/2302.06232v3
https://arxiv.org/pdf/2302.06232v3.pdf
https://github.com/nswa17/mmcl
true
true
false
pytorch
https://paperswithcode.com/paper/converting-anyone-s-emotion-towards-speaker
Converting Anyone's Emotion: Towards Speaker-Independent Emotional Voice Conversion
2005.07025
https://arxiv.org/abs/2005.07025v3
https://arxiv.org/pdf/2005.07025v3.pdf
https://github.com/KunZhou9646/Speaker-independent-emotional-voice-conversion-based-on-conditional-VAW-GAN-and-CWT
true
false
false
tf
https://paperswithcode.com/paper/a-recursive-skeletonization-factorization
A recursive skeletonization factorization based on strong admissibility
1609.08130
http://arxiv.org/abs/1609.08130v2
http://arxiv.org/pdf/1609.08130v2.pdf
https://github.com/klho/FLAM
true
true
false
none
https://paperswithcode.com/paper/autoconj-recognizing-and-exploiting-conjugacy
Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language
1811.11926
http://arxiv.org/abs/1811.11926v1
http://arxiv.org/pdf/1811.11926v1.pdf
https://github.com/google-research/autoconj
true
true
false
none
https://paperswithcode.com/paper/openmatch-open-set-semi-supervised-learning
OpenMatch: Open-Set Semi-supervised Learning with Open-set Consistency Regularization
null
http://proceedings.neurips.cc/paper/2021/hash/da11e8cd1811acb79ccf0fd62cd58f86-Abstract.html
http://proceedings.neurips.cc/paper/2021/file/da11e8cd1811acb79ccf0fd62cd58f86-Paper.pdf
https://github.com/VisionLearningGroup/OP_Match
true
true
false
pytorch
https://paperswithcode.com/paper/the-convolutional-tsetlin-machine
The Convolutional Tsetlin Machine
1905.09688
https://arxiv.org/abs/1905.09688v5
https://arxiv.org/pdf/1905.09688v5.pdf
https://github.com/cair/convolutional-tsetlin-machine
true
true
true
none
https://paperswithcode.com/paper/differentiable-learning-of-quantum-circuit
Differentiable Learning of Quantum Circuit Born Machine
1804.04168
http://arxiv.org/abs/1804.04168v1
http://arxiv.org/pdf/1804.04168v1.pdf
https://github.com/UnofficialJuliaMirrorSnapshots/Yao.jl-5872b779-8223-5990-8dd0-5abbb0748c8c
false
false
true
none
https://paperswithcode.com/paper/a-quantum-approximate-optimization-algorithm-1
A Quantum Approximate Optimization Algorithm
1411.4028
http://arxiv.org/abs/1411.4028v1
http://arxiv.org/pdf/1411.4028v1.pdf
https://github.com/UnofficialJuliaMirrorSnapshots/Yao.jl-5872b779-8223-5990-8dd0-5abbb0748c8c
false
false
true
none
https://paperswithcode.com/paper/bayesian-regression-and-bitcoin
Bayesian regression and Bitcoin
1410.1231
http://arxiv.org/abs/1410.1231v1
http://arxiv.org/pdf/1410.1231v1.pdf
https://github.com/raveenaaa/BitcoinPricing
false
false
true
none
https://paperswithcode.com/paper/learning-discrete-and-continuous-factors-of
Learning Discrete and Continuous Factors of Data via Alternating Disentanglement
1905.09432
https://arxiv.org/abs/1905.09432v1
https://arxiv.org/pdf/1905.09432v1.pdf
https://github.com/snu-mllab/DisentanglementICML19
true
true
false
tf
https://paperswithcode.com/paper/learning-to-prove-theorems-via-interacting
Learning to Prove Theorems via Interacting with Proof Assistants
1905.09381
https://arxiv.org/abs/1905.09381v1
https://arxiv.org/pdf/1905.09381v1.pdf
https://github.com/princeton-vl/CoqGym
true
true
true
pytorch
https://paperswithcode.com/paper/a-study-on-wrist-identification-for-forensic
A Study on Wrist Identification for Forensic Investigation
1910.03213
https://arxiv.org/abs/1910.03213v1
https://arxiv.org/pdf/1910.03213v1.pdf
https://github.com/matkowski-voy/Wrist-Identification-for-Forensic-Investigation
false
false
true
none
https://paperswithcode.com/paper/event-based-6-dof-camera-tracking-from
Event-based, 6-DOF Camera Tracking from Photometric Depth Maps
1607.03468
http://arxiv.org/abs/1607.03468v2
http://arxiv.org/pdf/1607.03468v2.pdf
https://github.com/uzh-rpg/event-based_vision_resources
true
true
false
pytorch
https://paperswithcode.com/paper/learning-attentions-residual-attentional
Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking
null
http://openaccess.thecvf.com/content_cvpr_2018/html/Wang_Learning_Attentions_Residual_CVPR_2018_paper.html
http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_Attentions_Residual_CVPR_2018_paper.pdf
https://github.com/HaHuangChan/RASNet
false
false
false
pytorch
https://paperswithcode.com/paper/debie-a-platform-for-implicit-and-explicit
DebIE: A Platform for Implicit and Explicit Debiasing of Word Embedding Spaces
2103.06598
https://arxiv.org/abs/2103.06598v1
https://arxiv.org/pdf/2103.06598v1.pdf
https://github.com/nfriedri/debie-command-line
false
false
false
none
https://paperswithcode.com/paper/support-vector-comparison-machines
Support vector comparison machines
1401.8008
https://arxiv.org/abs/1401.8008v3
https://arxiv.org/pdf/1401.8008v3.pdf
https://github.com/tdhock/rankSVMcompare
true
true
true
none
https://paperswithcode.com/paper/an-algorithm-for-optimal-partitioning-of-data
An Algorithm for Optimal Partitioning of Data on an Interval
math/0309285
https://arxiv.org/abs/math/0309285v2
https://arxiv.org/pdf/math/0309285v2.pdf
https://github.com/as4378/opart
false
false
true
none
https://paperswithcode.com/paper/statistical-mechanics-of-money
Statistical mechanics of money
cond-mat/0001432
https://arxiv.org/abs/cond-mat/0001432v4
https://arxiv.org/pdf/cond-mat/0001432v4.pdf
https://github.com/mortificador/economic_agents
false
false
true
none
https://paperswithcode.com/paper/a-data-exchange-standard-for-optical
A Data Exchange Standard for Optical (Visible/IR) Interferometry
astro-ph/0508185
https://arxiv.org/abs/astro-ph/0508185v1
https://arxiv.org/pdf/astro-ph/0508185v1.pdf
https://github.com/UnofficialJuliaMirrorSnapshots/OIFITS.jl-53eb397e-dec1-5dcf-8dc9-2db916067267
false
false
true
none
https://paperswithcode.com/paper/janossy-pooling-learning-deep-permutation
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs
1811.01900
http://arxiv.org/abs/1811.01900v3
http://arxiv.org/pdf/1811.01900v3.pdf
https://github.com/PurdueMINDS/JanossyPooling
true
true
true
pytorch
https://paperswithcode.com/paper/quantum-strategies
Quantum strategies
quant-ph/9804010
https://arxiv.org/abs/quant-ph/9804010v1
https://arxiv.org/pdf/quant-ph/9804010v1.pdf
https://github.com/msohaibalam/Link_to_Quantum_game
false
false
true
none
https://paperswithcode.com/paper/machine-learning-determination-of-dynamical
Machine learning determination of dynamical parameters: The Ising model case
1810.11503
http://arxiv.org/abs/1810.11503v1
http://arxiv.org/pdf/1810.11503v1.pdf
https://github.com/torfjelde/summer-project-2018
false
false
true
none
https://paperswithcode.com/paper/dancing-links
Dancing links
cs/0011047
https://arxiv.org/abs/cs/0011047v1
https://arxiv.org/pdf/cs/0011047v1.pdf
https://github.com/riceluxs1t/algorithmX-color-controls
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/LiliMeng/3D-ResNets-PyTorch
false
false
true
pytorch
https://paperswithcode.com/paper/mutual-information-between-discrete-and
Mutual Information between Discrete and Continuous Data Sets
null
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0087357
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0087357&type=printable
https://github.com/danielhomola/mifs
false
false
false
none
https://paperswithcode.com/paper/graphs-constraints-and-search-for-the
Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus
2210.09880
https://arxiv.org/abs/2210.09880v2
https://arxiv.org/pdf/2210.09880v2.pdf
https://github.com/khalil-research/arga-aaai23
true
true
true
none
https://paperswithcode.com/paper/enhancing-ai-assisted-writing-with-one-shot
Enhancing AI Assisted Writing with One-Shot Implicit Negative Feedback
2410.11009
https://arxiv.org/abs/2410.11009v1
https://arxiv.org/pdf/2410.11009v1.pdf
https://github.com/BenjaminTowle/NIFTY
true
false
false
pytorch
https://paperswithcode.com/paper/efficient-deformable-shape-correspondence-via
Efficient Deformable Shape Correspondence via Kernel Matching
1707.08991
http://arxiv.org/abs/1707.08991v3
http://arxiv.org/pdf/1707.08991v3.pdf
https://github.com/zorah/KernelMatching
true
true
true
none
https://paperswithcode.com/paper/learning-roi-transformer-for-oriented-object
Learning RoI Transformer for Oriented Object Detection in Aerial Images
null
http://openaccess.thecvf.com/content_CVPR_2019/html/Ding_Learning_RoI_Transformer_for_Oriented_Object_Detection_in_Aerial_Images_CVPR_2019_paper.html
http://openaccess.thecvf.com/content_CVPR_2019/papers/Ding_Learning_RoI_Transformer_for_Oriented_Object_Detection_in_Aerial_Images_CVPR_2019_paper.pdf
https://github.com/dingjiansw101/RoITransformer_DOTA
false
false
false
mxnet
https://paperswithcode.com/paper/depth-prediction-without-the-sensors
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos
1811.06152
http://arxiv.org/abs/1811.06152v1
http://arxiv.org/pdf/1811.06152v1.pdf
https://github.com/lukaszhalbiniak95/Projekt_RA
false
false
true
tf
https://paperswithcode.com/paper/teaching-deep-neural-networks-to-localize
Teaching deep neural networks to localize single molecules for super-resolution microscopy
1907.00770
https://arxiv.org/abs/1907.00770v2
https://arxiv.org/pdf/1907.00770v2.pdf
https://github.com/ZhuangLab/storm-analysis
true
true
false
none
https://paperswithcode.com/paper/190503329
Learning Embeddings into Entropic Wasserstein Spaces
1905.03329
https://arxiv.org/abs/1905.03329v1
https://arxiv.org/pdf/1905.03329v1.pdf
https://github.com/gabsens/Learning-Embeddings-into-Entropic-Wasserstein-Spaces-ENSAE
false
false
true
none
https://paperswithcode.com/paper/rafiki-machine-learning-as-an-analytics
Rafiki: Machine Learning as an Analytics Service System
1804.06087
http://arxiv.org/abs/1804.06087v1
http://arxiv.org/pdf/1804.06087v1.pdf
https://github.com/nginyc/rafiki
false
false
false
none
https://paperswithcode.com/paper/contrastive-multi-view-representation
Contrastive Multi-View Representation Learning on Graphs
2006.05582
https://arxiv.org/abs/2006.05582v1
https://arxiv.org/pdf/2006.05582v1.pdf
https://github.com/hengruizhang98/mvgrl
false
false
true
pytorch
https://paperswithcode.com/paper/tropical-homology
Tropical Homology
1604.01838
http://arxiv.org/abs/1604.01838v2
http://arxiv.org/pdf/1604.01838v2.pdf
https://github.com/lkastner/cellularSheaves
false
false
true
none
https://paperswithcode.com/paper/personalization-and-optimization-of-decision
Personalized Treatment Selection using Causal Heterogeneity
1901.10550
https://arxiv.org/abs/1901.10550v4
https://arxiv.org/pdf/1901.10550v4.pdf
https://github.com/tuye0305/kdd2019prophet
true
true
true
none
https://paperswithcode.com/paper/electro-magnetic-side-channel-attack-through
Electro-Magnetic Side-Channel Attack Through Learned Denoising and Classification
1910.07201
https://arxiv.org/abs/1910.07201v1
https://arxiv.org/pdf/1910.07201v1.pdf
https://github.com/opendenoising/interception_dataset
true
true
true
none
https://paperswithcode.com/paper/batch-feature-erasing-for-person-re
Batch DropBlock Network for Person Re-identification and Beyond
1811.07130
https://arxiv.org/abs/1811.07130v3
https://arxiv.org/pdf/1811.07130v3.pdf
https://github.com/daizuozhuo/batch-feature-erasing-network
false
false
true
pytorch
https://paperswithcode.com/paper/a-class-of-two-sample-nonparametric
A class of two-sample nonparametric statistics for binary and time-to-event outcomes
2002.01369
https://arxiv.org/abs/2002.01369v2
https://arxiv.org/pdf/2002.01369v2.pdf
https://github.com/MartaBofillRoig/SurvBin
true
true
true
none
https://paperswithcode.com/paper/holistically-nested-edge-detection
Holistically-Nested Edge Detection
1504.06375
http://arxiv.org/abs/1504.06375v2
http://arxiv.org/pdf/1504.06375v2.pdf
https://github.com/ajinkya933/understanding-tensorflow-graph
false
false
true
tf
https://paperswithcode.com/paper/res2net-a-new-multi-scale-backbone
Res2Net: A New Multi-scale Backbone Architecture
1904.01169
https://arxiv.org/abs/1904.01169v3
https://arxiv.org/pdf/1904.01169v3.pdf
https://github.com/gasvn/Res2Net
false
false
true
pytorch
https://paperswithcode.com/paper/dam-reservoir-extraction-from-remote-sensing
Dam reservoir extraction from remote sensing imagery using tailored metric learning strategies
2207.05807
https://arxiv.org/abs/2207.05807v1
https://arxiv.org/pdf/2207.05807v1.pdf
https://github.com/c8241998/dam-reservoir-extraction
true
true
false
tf
https://paperswithcode.com/paper/graph-kernels-based-on-linear-patterns
Graph Kernels Based on Linear Patterns: Theoretical and Experimental Comparisons
null
https://hal-normandie-univ.archives-ouvertes.fr/hal-02053946/
https://hal-normandie-univ.archives-ouvertes.fr/hal-02053946/document
https://github.com/jajupmochi/py-graph
false
true
false
none
https://paperswithcode.com/paper/a-plot-is-worth-a-thousand-words-model
A Plot is Worth a Thousand Words: Model Information Stealing Attacks via Scientific Plots
2302.11982
https://arxiv.org/abs/2302.11982v1
https://arxiv.org/pdf/2302.11982v1.pdf
https://github.com/boz083/plot_steal
true
true
false
pytorch
https://paperswithcode.com/paper/large-scale-correlation-clustering
Large Scale Correlation Clustering Optimization
1112.2903
http://arxiv.org/abs/1112.2903v1
http://arxiv.org/pdf/1112.2903v1.pdf
https://github.com/nveldt/LamCC
false
false
true
none
https://paperswithcode.com/paper/simpler-non-parametric-methods-provide-as-1
Simpler non-parametric methods provide as good or better results to multiple-instance learning.
null
https://www.cv-foundation.org/openaccess/content_iccv_2015/html/Venkatesan_Simpler_Non-Parametric_Methods_ICCV_2015_paper.html
https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Venkatesan_Simpler_Non-Parametric_Methods_ICCV_2015_paper.pdf
https://github.com/ragavvenkatesan/np-mil
false
false
false
none
https://paperswithcode.com/paper/160703045
Shared Subspace Models for Multi-Group Covariance Estimation
1607.03045
http://arxiv.org/abs/1607.03045v3
http://arxiv.org/pdf/1607.03045v3.pdf
https://github.com/afranks86/shared-subspace
true
true
true
none
https://paperswithcode.com/paper/addressing-function-approximation-error-in
Addressing Function Approximation Error in Actor-Critic Methods
1802.09477
http://arxiv.org/abs/1802.09477v3
http://arxiv.org/pdf/1802.09477v3.pdf
https://github.com/ccolas/rl_stats
false
false
true
none
https://paperswithcode.com/paper/language-models-are-unsupervised-multitask
Language Models are Unsupervised Multitask Learners
null
https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf
https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf
https://github.com/huggingface/swift-coreml-transformers
false
false
false
pytorch
https://paperswithcode.com/paper/high-resolution-of-particle-contacts-via
High-resolution of particle contacts via fluorophore exclusion in deep-imaging of jammed colloidal packings
1708.04702
https://arxiv.org/abs/1708.04702v1
https://arxiv.org/pdf/1708.04702v1.pdf
https://github.com/enyombi/3D_particle_tracking
false
false
true
none
https://paperswithcode.com/paper/learning-to-synthesize-a-4d-rgbd-light-field
Learning to Synthesize a 4D RGBD Light Field from a Single Image
1708.03292
http://arxiv.org/abs/1708.03292v1
http://arxiv.org/pdf/1708.03292v1.pdf
https://github.com/pratulsrinivasan/Local_Light_Field_Synthesis
false
false
true
tf
https://paperswithcode.com/paper/an-sdp-based-branch-and-cut-algorithm-for
A Semidefinite Programming-Based Branch-and-Cut Algorithm for Biclustering
2403.11351
https://arxiv.org/abs/2403.11351v3
https://arxiv.org/pdf/2403.11351v3.pdf
https://github.com/antoniosudoso/bicl-sdp
true
true
false
none
https://paperswithcode.com/paper/hog-lbp-and-svm-based-traffic-density
HOG, LBP and SVM based Traffic Density Estimation at Intersection
2005.01770
https://arxiv.org/abs/2005.01770v1
https://arxiv.org/pdf/2005.01770v1.pdf
https://github.com/DevashishPrasad/Smart-Traffic-Junction
true
true
true
none
https://paperswithcode.com/paper/show-attend-and-tell-neural-image-caption
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
1502.03044
http://arxiv.org/abs/1502.03044v3
http://arxiv.org/pdf/1502.03044v3.pdf
https://github.com/Pillercottrer/radcap_project
false
false
true
pytorch
https://paperswithcode.com/paper/cmrnet-map-and-camera-agnostic-monocular
CMRNet++: Map and Camera Agnostic Monocular Visual Localization in LiDAR Maps
2004.13795
https://arxiv.org/abs/2004.13795v2
https://arxiv.org/pdf/2004.13795v2.pdf
https://github.com/catta202000/CMRNet
false
false
true
pytorch
https://paperswithcode.com/paper/thresholded-adaptive-validation-tuning-the
Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery
2005.00466
https://arxiv.org/abs/2005.00466v2
https://arxiv.org/pdf/2005.00466v2.pdf
https://github.com/MikeLasz/thav.glasso
true
true
false
none
https://paperswithcode.com/paper/sok-of-used-cryptography-in-blockchain
SoK of Used Cryptography in Blockchain
1906.08609
https://arxiv.org/abs/1906.08609v3
https://arxiv.org/pdf/1906.08609v3.pdf
https://github.com/MayankRaikwar/SoK-of-Used-Cryptography-in-Blockchain
false
false
true
none
https://paperswithcode.com/paper/very-deep-convolutional-networks-for-large
Very Deep Convolutional Networks for Large-Scale Image Recognition
1409.1556
http://arxiv.org/abs/1409.1556v6
http://arxiv.org/pdf/1409.1556v6.pdf
https://github.com/sitegui/ceci-nest-pas-un-chat
false
false
true
tf
https://paperswithcode.com/paper/identity-mappings-in-deep-residual-networks
Identity Mappings in Deep Residual Networks
1603.05027
http://arxiv.org/abs/1603.05027v3
http://arxiv.org/pdf/1603.05027v3.pdf
https://github.com/sitegui/ceci-nest-pas-un-chat
false
false
true
tf
https://paperswithcode.com/paper/a-bayesian-inspired-deep-learning-semi
A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping
2005.11930
https://arxiv.org/abs/2005.11930v2
https://arxiv.org/pdf/2005.11930v2.pdf
https://github.com/benjaminmlucas/sourcerer
true
true
false
pytorch
https://paperswithcode.com/paper/sensitivity-and-dimensionality-of-atomic
Sensitivity and Dimensionality of Atomic Environment Representations used for Machine Learning Interatomic Potentials
2006.01915
https://arxiv.org/abs/2006.01915v2
https://arxiv.org/pdf/2006.01915v2.pdf
https://github.com/DescriptorZoo/AMP.jl
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/Qengineering/MobileNetV2_YOLOV3_ncnn
false
false
true
none
https://paperswithcode.com/paper/mxnet-a-flexible-and-efficient-machine
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
1512.01274
http://arxiv.org/abs/1512.01274v1
http://arxiv.org/pdf/1512.01274v1.pdf
https://github.com/ctuning/ck-mxnet
false
false
true
mxnet
https://paperswithcode.com/paper/score-based-data-generation-for-eeg-spatial
Score-Based Data Generation for EEG Spatial Covariance Matrices: Towards Boosting BCI Performance
2302.11410
https://arxiv.org/abs/2302.11410v3
https://arxiv.org/pdf/2302.11410v3.pdf
https://github.com/GeometricBCI/Tensor-CSPNet-and-Graph-CSPNet
true
true
false
pytorch
https://paperswithcode.com/paper/190910481
Cross-Lingual Natural Language Generation via Pre-Training
1909.10481
https://arxiv.org/abs/1909.10481v3
https://arxiv.org/pdf/1909.10481v3.pdf
https://github.com/CZWin32768/xnlg
true
true
true
pytorch