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

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/agile-multi-source-free-domain-adaptation
Agile Multi-Source-Free Domain Adaptation
2403.05062
https://arxiv.org/abs/2403.05062v1
https://arxiv.org/pdf/2403.05062v1.pdf
https://github.com/tl-uestc/bi-aten
true
true
true
pytorch
https://paperswithcode.com/paper/sa-solver-stochastic-adams-solver-for-fast
SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models
2309.05019
https://arxiv.org/abs/2309.05019v2
https://arxiv.org/pdf/2309.05019v2.pdf
https://github.com/scxue/SA-Solver
true
false
true
pytorch
https://paperswithcode.com/paper/can-language-models-solve-graph-problems-in
Can Language Models Solve Graph Problems in Natural Language?
2305.10037
https://arxiv.org/abs/2305.10037v3
https://arxiv.org/pdf/2305.10037v3.pdf
https://github.com/Samyu0304/thought-propagation
false
false
true
none
https://paperswithcode.com/paper/neural-message-passing-for-quantum-chemistry
Neural Message Passing for Quantum Chemistry
1704.01212
http://arxiv.org/abs/1704.01212v2
http://arxiv.org/pdf/1704.01212v2.pdf
https://github.com/Samyu0304/thought-propagation
false
false
true
none
https://paperswithcode.com/paper/language-models-are-few-shot-learners
Language Models are Few-Shot Learners
2005.14165
https://arxiv.org/abs/2005.14165v4
https://arxiv.org/pdf/2005.14165v4.pdf
https://github.com/Samyu0304/thought-propagation
false
false
true
none
https://paperswithcode.com/paper/efficient-conditional-diffusion-model-with
Efficient Conditional Diffusion Model with Probability Flow Sampling for Image Super-resolution
2404.10688
https://arxiv.org/abs/2404.10688v1
https://arxiv.org/pdf/2404.10688v1.pdf
https://github.com/yuan-yutao/ecdp
true
true
false
pytorch
https://paperswithcode.com/paper/sensory-attenuation-develops-as-a-result-of
Emergence of sensory attenuation based upon the free-energy principle
2111.02666
https://arxiv.org/abs/2111.02666v3
https://arxiv.org/pdf/2111.02666v3.pdf
https://github.com/h-idei/pvrnn_sa
true
true
false
pytorch
https://paperswithcode.com/paper/rsmamba-remote-sensing-image-classification
RSMamba: Remote Sensing Image Classification with State Space Model
2403.19654
https://arxiv.org/abs/2403.19654v1
https://arxiv.org/pdf/2403.19654v1.pdf
https://github.com/KyanChen/RSMamba
true
true
true
pytorch
https://paperswithcode.com/paper/wavelet-based-fourier-information-interaction
Wavelet-based Fourier Information Interaction with Frequency Diffusion Adjustment for Underwater Image Restoration
2311.16845
https://arxiv.org/abs/2311.16845v1
https://arxiv.org/pdf/2311.16845v1.pdf
https://github.com/zhihefang/wf-diff
true
true
true
pytorch
https://paperswithcode.com/paper/comparative-evaluation-of-earthquake
Comparative evaluation of earthquake forecasting models: An application to Italy
2405.10712
https://arxiv.org/abs/2405.10712v1
https://arxiv.org/pdf/2405.10712v1.pdf
https://github.com/jbrehmer42/Earthquakes_Italy
true
false
true
none
https://paperswithcode.com/paper/voice-transformer-network-sequence-to
Voice Transformer Network: Sequence-to-Sequence Voice Conversion Using Transformer with Text-to-Speech Pretraining
1912.06813
https://arxiv.org/abs/1912.06813v1
https://arxiv.org/pdf/1912.06813v1.pdf
https://github.com/unilight/seq2seq-vc
false
false
true
pytorch
https://paperswithcode.com/paper/pretraining-techniques-for-sequence-to
Pretraining Techniques for Sequence-to-Sequence Voice Conversion
2008.03088
https://arxiv.org/abs/2008.03088v1
https://arxiv.org/pdf/2008.03088v1.pdf
https://github.com/unilight/seq2seq-vc
false
false
true
pytorch
https://paperswithcode.com/paper/dynamic-implicit-image-function-for-efficient
Dynamic Implicit Image Function for Efficient Arbitrary-Scale Image Representation
2306.12321
https://arxiv.org/abs/2306.12321v2
https://arxiv.org/pdf/2306.12321v2.pdf
https://github.com/hezongyao/diif
true
true
true
pytorch
https://paperswithcode.com/paper/decoupling-static-and-hierarchical-motion
Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation
2404.03645
https://arxiv.org/abs/2404.03645v1
https://arxiv.org/pdf/2404.03645v1.pdf
https://github.com/heshuting555/dshmp
true
true
true
pytorch
https://paperswithcode.com/paper/noise-robust-keyword-spotting-through-self
Noise-Robust Keyword Spotting through Self-supervised Pretraining
2403.18560
https://arxiv.org/abs/2403.18560v1
https://arxiv.org/pdf/2403.18560v1.pdf
https://github.com/aau-es-ml/ssl_noise-robust_kws
true
true
false
pytorch
https://paperswithcode.com/paper/improving-label-deficient-keyword-spotting
Improving Label-Deficient Keyword Spotting Through Self-Supervised Pretraining
2210.01703
https://arxiv.org/abs/2210.01703v3
https://arxiv.org/pdf/2210.01703v3.pdf
https://github.com/aau-es-ml/ssl_noise-robust_kws
false
false
true
pytorch
https://paperswithcode.com/paper/keyword-transformer-a-self-attention-model
Keyword Transformer: A Self-Attention Model for Keyword Spotting
2104.00769
https://arxiv.org/abs/2104.00769v3
https://arxiv.org/pdf/2104.00769v3.pdf
https://github.com/aau-es-ml/ssl_noise-robust_kws
false
false
true
pytorch
https://paperswithcode.com/paper/data2vec-a-general-framework-for-self-1
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
2202.03555
https://arxiv.org/abs/2202.03555v3
https://arxiv.org/pdf/2202.03555v3.pdf
https://github.com/aau-es-ml/ssl_noise-robust_kws
false
false
true
pytorch
https://paperswithcode.com/paper/estimating-aging-curves-using-multiple
Filling the Gaps: A Multiple Imputation Approach to Estimating Aging Curves in Baseball
2210.02383
https://arxiv.org/abs/2210.02383v3
https://arxiv.org/pdf/2210.02383v3.pdf
https://github.com/qntkhvn/aging
true
true
false
none
https://paperswithcode.com/paper/rho-1-not-all-tokens-are-what-you-need
Rho-1: Not All Tokens Are What You Need
2404.07965
https://arxiv.org/abs/2404.07965v4
https://arxiv.org/pdf/2404.07965v4.pdf
https://github.com/ZubinGou/rho
false
false
true
none
https://paperswithcode.com/paper/on-temporal-references-in-emergent
It's About Time: Temporal References in Emergent Communication
2310.06555
https://arxiv.org/abs/2310.06555v2
https://arxiv.org/pdf/2310.06555v2.pdf
https://github.com/olipinski/trg
true
true
false
pytorch
https://paperswithcode.com/paper/mdvit-multi-domain-vision-transformer-for
MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets
2307.02100
https://arxiv.org/abs/2307.02100v3
https://arxiv.org/pdf/2307.02100v3.pdf
https://github.com/siyi-wind/tip
false
false
true
pytorch
https://paperswithcode.com/paper/probing-for-multilingual-numerical
Probing for Multilingual Numerical Understanding in Transformer-Based Language Models
2010.06666
https://arxiv.org/abs/2010.06666v1
https://arxiv.org/pdf/2010.06666v1.pdf
https://github.com/dj1121/tlm_num_probe
true
true
false
pytorch
https://paperswithcode.com/paper/game-based-platforms-for-artificial
Games for Artificial Intelligence Research: A Review and Perspectives
2304.13269
https://arxiv.org/abs/2304.13269v4
https://arxiv.org/pdf/2304.13269v4.pdf
https://github.com/sustechgameai/gameai-platforms
true
true
false
none
https://paperswithcode.com/paper/adaptive-multi-head-contrastive-learning
Adaptive Multi-head Contrastive Learning
2310.05615
https://arxiv.org/abs/2310.05615v3
https://arxiv.org/pdf/2310.05615v3.pdf
https://github.com/leiwangr/cl
true
true
false
pytorch
https://paperswithcode.com/paper/pypots-a-python-toolbox-for-data-mining-on
PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series
2305.18811
https://arxiv.org/abs/2305.18811v1
https://arxiv.org/pdf/2305.18811v1.pdf
https://github.com/WenjieDu/PyGrinder
true
false
true
pytorch
https://paperswithcode.com/paper/mirage-model-agnostic-graph-distillation-for
Mirage: Model-Agnostic Graph Distillation for Graph Classification
2310.09486
https://arxiv.org/abs/2310.09486v4
https://arxiv.org/pdf/2310.09486v4.pdf
https://github.com/idea-iitd/mirage
true
true
false
pytorch
https://paperswithcode.com/paper/configurable-safety-tuning-of-language-models
Configurable Safety Tuning of Language Models with Synthetic Preference Data
2404.00495
https://arxiv.org/abs/2404.00495v1
https://arxiv.org/pdf/2404.00495v1.pdf
https://github.com/vicgalle/configurable-safety-tuning
true
true
true
pytorch
https://paperswithcode.com/paper/selfpose3d-self-supervised-multi-person-multi
SelfPose3d: Self-Supervised Multi-Person Multi-View 3d Pose Estimation
2404.02041
https://arxiv.org/abs/2404.02041v2
https://arxiv.org/pdf/2404.02041v2.pdf
https://github.com/camma-public/selfpose3d
true
true
true
pytorch
https://paperswithcode.com/paper/cameractrl-enabling-camera-control-for-text
CameraCtrl: Enabling Camera Control for Text-to-Video Generation
2404.02101
https://arxiv.org/abs/2404.02101v1
https://arxiv.org/pdf/2404.02101v1.pdf
https://github.com/hehao13/cameractrl
true
true
true
pytorch
https://paperswithcode.com/paper/learning-to-rank-patches-for-unbiased-image
Learning to Rank Patches for Unbiased Image Redundancy Reduction
2404.00680
https://arxiv.org/abs/2404.00680v2
https://arxiv.org/pdf/2404.00680v2.pdf
https://github.com/irslu/ltrp
true
true
false
pytorch
https://paperswithcode.com/paper/dmssn-distilled-mixed-spectral-spatial
DMSSN: Distilled Mixed Spectral-Spatial Network for Hyperspectral Salient Object Detection
2404.00694
https://arxiv.org/abs/2404.00694v1
https://arxiv.org/pdf/2404.00694v1.pdf
https://github.com/anonymous0519/hsod-bit
true
true
false
pytorch
https://paperswithcode.com/paper/humanizing-machine-generated-content-evading
Humanizing Machine-Generated Content: Evading AI-Text Detection through Adversarial Attack
2404.01907
https://arxiv.org/abs/2404.01907v1
https://arxiv.org/pdf/2404.01907v1.pdf
https://github.com/zhouying20/hmgc
true
true
true
pytorch
https://paperswithcode.com/paper/diffusion-models-for-computational-design-at
Automating Computational Design with Generative AI
2307.02511
https://arxiv.org/abs/2307.02511v2
https://arxiv.org/pdf/2307.02511v2.pdf
https://github.com/ai4sc/bim-diffusion-models
true
true
false
none
https://paperswithcode.com/paper/a-new-benchmark-and-model-for-challenging
A New Benchmark and Model for Challenging Image Manipulation Detection
2311.14218
https://arxiv.org/abs/2311.14218v2
https://arxiv.org/pdf/2311.14218v2.pdf
https://github.com/zhenfeiz/cimd
true
true
true
none
https://paperswithcode.com/paper/a-transformer-approach-for-electricity-price
A Transformer approach for Electricity Price Forecasting
2403.16108
https://arxiv.org/abs/2403.16108v2
https://arxiv.org/pdf/2403.16108v2.pdf
https://github.com/osllogon/epf-transformers
true
true
true
pytorch
https://paperswithcode.com/paper/robust-offline-policy-evaluation-and
Robust Offline Reinforcement learning with Heavy-Tailed Rewards
2310.18715
https://arxiv.org/abs/2310.18715v2
https://arxiv.org/pdf/2310.18715v2.pdf
https://github.com/mamba413/room
true
true
true
pytorch
https://paperswithcode.com/paper/long-form-evaluation-of-model-editing
Long-form evaluation of model editing
2402.09394
https://arxiv.org/abs/2402.09394v2
https://arxiv.org/pdf/2402.09394v2.pdf
https://github.com/domenicrosati/longform-evaluation-model-editing
true
true
true
pytorch
https://paperswithcode.com/paper/cages-cost-aware-gradient-entropy-search-for
CAGES: Cost-Aware Gradient Entropy Search for Efficient Local Multi-Fidelity Bayesian Optimization
2405.07760
https://arxiv.org/abs/2405.07760v1
https://arxiv.org/pdf/2405.07760v1.pdf
https://github.com/PaulsonLab/CAGES
true
true
true
pytorch
https://paperswithcode.com/paper/enhancing-semantic-fidelity-in-text-to-image
Enhancing Semantic Fidelity in Text-to-Image Synthesis: Attention Regulation in Diffusion Models
2403.06381
https://arxiv.org/abs/2403.06381v1
https://arxiv.org/pdf/2403.06381v1.pdf
https://github.com/yangzhang-v5/attention_regulation
true
true
true
pytorch
https://paperswithcode.com/paper/eye-gaze-guided-multi-modal-alignment
Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning
2403.12416
https://arxiv.org/abs/2403.12416v3
https://arxiv.org/pdf/2403.12416v3.pdf
https://github.com/momarky/egma
true
true
true
pytorch
https://paperswithcode.com/paper/burstattention-an-efficient-distributed
BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences
2403.09347
https://arxiv.org/abs/2403.09347v4
https://arxiv.org/pdf/2403.09347v4.pdf
https://github.com/MayDomine/Burst-Attention
true
false
true
pytorch
https://paperswithcode.com/paper/lucid-llm-generated-utterances-for-complex
LUCID: LLM-Generated Utterances for Complex and Interesting Dialogues
2403.00462
https://arxiv.org/abs/2403.00462v2
https://arxiv.org/pdf/2403.00462v2.pdf
https://github.com/apple/ml-lucid-datagen
true
true
true
none
https://paperswithcode.com/paper/learning-dynamic-graphs-from-all-contextual
Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit Forecasting
2306.15927
https://arxiv.org/abs/2306.15927v2
https://arxiv.org/pdf/2306.15927v2.pdf
https://github.com/USC-InfoLab/busyness-graph-neural-network
true
false
false
pytorch
https://paperswithcode.com/paper/syren-new-precise-formulae-for-the-linear-and
syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy
2410.14623
https://arxiv.org/abs/2410.14623v1
https://arxiv.org/pdf/2410.14623v1.pdf
https://github.com/deaglanbartlett/symbolic_pofk
true
false
true
pytorch
https://paperswithcode.com/paper/beyond-autoregression-discrete-diffusion-for
Beyond Autoregression: Discrete Diffusion for Complex Reasoning and Planning
2410.14157
https://arxiv.org/abs/2410.14157v1
https://arxiv.org/pdf/2410.14157v1.pdf
https://github.com/HKUNLP/diffusion-vs-ar
true
false
true
pytorch
https://paperswithcode.com/paper/the-why-in-business-processes-discovery-of
The WHY in Business Processes: Discovery of Causal Execution Dependencies
2310.14975
https://arxiv.org/abs/2310.14975v3
https://arxiv.org/pdf/2310.14975v3.pdf
https://github.com/ibm/sax4bpm
false
false
true
none
https://paperswithcode.com/paper/how-well-can-large-language-models-explain
How well can a large language model explain business processes as perceived by users?
2401.12846
https://arxiv.org/abs/2401.12846v4
https://arxiv.org/pdf/2401.12846v4.pdf
https://github.com/ibm/sax4bpm
true
true
true
none
https://paperswithcode.com/paper/geot-tensor-centric-library-for-graph-neural
GeoT: Tensor Centric Library for Graph Neural Network via Efficient Segment Reduction on GPU
2404.03019
https://arxiv.org/abs/2404.03019v2
https://arxiv.org/pdf/2404.03019v2.pdf
https://github.com/fishmingyu/geot
true
true
false
pytorch
https://paperswithcode.com/paper/lampilot-an-open-benchmark-dataset-for
LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs
2312.04372
https://arxiv.org/abs/2312.04372v2
https://arxiv.org/pdf/2312.04372v2.pdf
https://github.com/purduedigitaltwin/lampilot
true
true
true
none
https://paperswithcode.com/paper/sok-unintended-interactions-among-machine
SoK: Unintended Interactions among Machine Learning Defenses and Risks
2312.04542
https://arxiv.org/abs/2312.04542v2
https://arxiv.org/pdf/2312.04542v2.pdf
https://github.com/ssg-research/sok-unintended-interactions
true
true
false
pytorch
https://paperswithcode.com/paper/differentiable-instruction-optimization-for
Differentiable Instruction Optimization for Cross-Task Generalization
2306.10098
https://arxiv.org/abs/2306.10098v1
https://arxiv.org/pdf/2306.10098v1.pdf
https://github.com/misonuma/instopt
true
true
false
pytorch
https://paperswithcode.com/paper/bcamirs-at-semeval-2024-task-4-beyond-words-a
BCAmirs at SemEval-2024 Task 4: Beyond Words: A Multimodal and Multilingual Exploration of Persuasion in Memes
2404.03022
https://arxiv.org/abs/2404.03022v2
https://arxiv.org/pdf/2404.03022v2.pdf
https://github.com/amirabaskohi/beyond-words-a-multimodal-exploration-of-persuasion-in-memes
true
true
true
pytorch
https://paperswithcode.com/paper/uncertainty-estimation-for-path-loss-and
Uncertainty Estimation for Path Loss and Radio Metric Models
2501.06308
https://arxiv.org/abs/2501.06308v1
https://arxiv.org/pdf/2501.06308v1.pdf
https://github.com/ic-crc/uncertainty-estimation
true
true
true
none
https://paperswithcode.com/paper/increase-inductive-graph-representation
INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging
2302.02738
https://arxiv.org/abs/2302.02738v1
https://arxiv.org/pdf/2302.02738v1.pdf
https://github.com/Aminsheykh98/INCREASE-pytorch
false
false
false
pytorch
https://paperswithcode.com/paper/visualizing-the-loss-landscape-of-neural-nets
Visualizing the Loss Landscape of Neural Nets
1712.09913
http://arxiv.org/abs/1712.09913v3
http://arxiv.org/pdf/1712.09913v3.pdf
https://github.com/StephenThacker/Visualiation-of-Loss-Function
false
false
true
tf
https://paperswithcode.com/paper/multiple-environment-self-adaptive-network
Multiple-environment Self-adaptive Network for Aerial-view Geo-localization
2204.08381
https://arxiv.org/abs/2204.08381v2
https://arxiv.org/pdf/2204.08381v2.pdf
https://github.com/wtyhub/MuseNet
true
false
true
pytorch
https://paperswithcode.com/paper/challenges-for-reinforcement-learning-in-1
Challenges for Reinforcement Learning in Quantum Circuit Design
2312.11337
https://arxiv.org/abs/2312.11337v3
https://arxiv.org/pdf/2312.11337v3.pdf
https://github.com/philippaltmann/qcd
true
true
true
none
https://paperswithcode.com/paper/on-the-trustworthiness-of-generative
On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
2502.14296
https://arxiv.org/abs/2502.14296v3
https://arxiv.org/pdf/2502.14296v3.pdf
https://github.com/thuccslab/figstep
false
false
true
none
https://paperswithcode.com/paper/large-language-models-for-in-context-student
Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming
2310.10690
https://arxiv.org/abs/2310.10690v3
https://arxiv.org/pdf/2310.10690v3.pdf
https://github.com/machine-teaching-group/edm2024-llm-student-modeling
true
false
false
none
https://paperswithcode.com/paper/multi-objective-transmission-expansion-an
Multi-Objective Transmission Expansion: An Offshore Wind Power Integration Case Study
2311.09563
https://arxiv.org/abs/2311.09563v3
https://arxiv.org/pdf/2311.09563v3.pdf
https://github.com/sarojkhanal/motep-osw
true
true
true
none
https://paperswithcode.com/paper/antiferromagnetic-and-bond-order-wave-phases
Antiferromagnetic and bond-order-wave phases in the half-filled two-dimensional optical Su-Schrieffer-Heeger-Hubbard model
2502.14196
https://arxiv.org/abs/2502.14196v1
https://arxiv.org/pdf/2502.14196v1.pdf
https://github.com/smoqysuite/smoqydqmc.jl
true
false
false
none
https://paperswithcode.com/paper/deep-reinforcement-learning-for-personalized-1
Deep Reinforcement Learning for Personalized Diagnostic Decision Pathways Using Electronic Health Records: A Comparative Study on Anemia and Systemic Lupus Erythematosus
2404.05913
https://arxiv.org/abs/2404.05913v1
https://arxiv.org/pdf/2404.05913v1.pdf
https://github.com/lilly-muyama/deep_rl_diagnosis_pathways
true
true
false
tf
https://paperswithcode.com/paper/classification-of-breast-cancer
Classification of Breast Cancer Histopathology Images using a Modified Supervised Contrastive Learning Method
2405.03642
https://arxiv.org/abs/2405.03642v2
https://arxiv.org/pdf/2405.03642v2.pdf
https://github.com/matinamehdizadeh/Breast-Cancer-Detection
true
true
false
pytorch
https://paperswithcode.com/paper/consistent-point-orientation-for-manifold
Consistent Point Orientation for Manifold Surfaces via Boundary Integration
2407.03165
https://arxiv.org/abs/2407.03165v1
https://arxiv.org/pdf/2407.03165v1.pdf
https://github.com/liuweizhou319/bim
true
true
false
none
https://paperswithcode.com/paper/a-high-order-conservative-cut-finite-element
A High-Order Conservative Cut Finite Element Method for Problems in Time-Dependent Domains
2404.10756
https://arxiv.org/abs/2404.10756v3
https://arxiv.org/pdf/2404.10756v3.pdf
https://github.com/cutfem/cutfem-library
true
true
false
none
https://paperswithcode.com/paper/two-stages-domain-invariant-representation
Two stages domain invariant representation learners solve the large co-variate shift in unsupervised domain adaptation with two dimensional data domains
2412.04682
https://arxiv.org/abs/2412.04682v1
https://arxiv.org/pdf/2412.04682v1.pdf
https://github.com/oh-yu/domain-invariant-learning
true
false
true
pytorch
https://paperswithcode.com/paper/bertweet-a-pre-trained-language-model-for
BERTweet: A pre-trained language model for English Tweets
2005.10200
https://arxiv.org/abs/2005.10200v2
https://arxiv.org/pdf/2005.10200v2.pdf
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/bertweet
false
false
false
mindspore
https://paperswithcode.com/paper/when-do-prompting-and-prefix-tuning-work-a
When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations
2310.19698
https://arxiv.org/abs/2310.19698v2
https://arxiv.org/pdf/2310.19698v2.pdf
https://github.com/aleksandarpetrov/prefix-tuning-theory
true
true
true
pytorch
https://paperswithcode.com/paper/raffesdg-random-frequency-filtering-enabled
RaffeSDG: Random Frequency Filtering enabled Single-source Domain Generalization for Medical Image Segmentation
2405.01228
https://arxiv.org/abs/2405.01228v2
https://arxiv.org/pdf/2405.01228v2.pdf
https://github.com/liamheng/non-iid_medical_image_segmentation
true
true
true
pytorch
https://paperswithcode.com/paper/hypothesis-testing-using-causal-and-causal
Causal Structural Hypothesis Testing and Data Generation Models
2210.11275
https://arxiv.org/abs/2210.11275v2
https://arxiv.org/pdf/2210.11275v2.pdf
https://github.com/sunaybhat1/causal-structural-hypothesis-testing
true
true
true
pytorch
https://paperswithcode.com/paper/q8bert-quantized-8bit-bert
Q8BERT: Quantized 8Bit BERT
1910.06188
https://arxiv.org/abs/1910.06188v2
https://arxiv.org/pdf/1910.06188v2.pdf
https://github.com/iabd/QuantizedNMT
false
false
true
pytorch
https://paperswithcode.com/paper/medoid-silhouette-clustering-with-automatic
Medoid Silhouette clustering with automatic cluster number selection
2309.03751
https://arxiv.org/abs/2309.03751v1
https://arxiv.org/pdf/2309.03751v1.pdf
https://github.com/kno10/python-kmedoids
false
false
true
none
https://paperswithcode.com/paper/learning-based-video-motion-magnification
Learning-based Video Motion Magnification
1804.02684
http://arxiv.org/abs/1804.02684v3
http://arxiv.org/pdf/1804.02684v3.pdf
https://github.com/ZhengPeng7/motion_magnification_learning-based
false
false
true
pytorch
https://paperswithcode.com/paper/harnessing-data-and-physics-for-deep-learning
Deep learning phase recovery: data-driven, physics-driven, or combining both?
2404.01360
https://arxiv.org/abs/2404.01360v2
https://arxiv.org/pdf/2404.01360v2.pdf
https://github.com/kqwang/DLPR
true
true
true
pytorch
https://paperswithcode.com/paper/symmetric-observations-without-symmetric
Symmetric observations without symmetric causal explanations
2502.14950
https://arxiv.org/abs/2502.14950v1
https://arxiv.org/pdf/2502.14950v1.pdf
https://github.com/apozas/symmetric-causal
true
true
true
none
https://paperswithcode.com/paper/sea-land-cloud-segmentation-in-satellite
Semantic Segmentation in Satellite Hyperspectral Imagery by Deep Learning
2310.16210
https://arxiv.org/abs/2310.16210v4
https://arxiv.org/pdf/2310.16210v4.pdf
https://github.com/ntnu-smallsat-lab/s_l_c_segm_hyp_img
true
true
true
tf
https://paperswithcode.com/paper/when-big-data-actually-are-low-rank-or
When big data actually are low-rank, or entrywise approximation of certain function-generated matrices
2407.03250
https://arxiv.org/abs/2407.03250v4
https://arxiv.org/pdf/2407.03250v4.pdf
https://github.com/sbudzinskiy/low-rank-big-data
true
true
true
none
https://paperswithcode.com/paper/ampic-adaptive-model-predictive-ising
Traffic signal optimization in large-scale urban road networks: an adaptive-predictive controller using Ising models
2406.03690
https://arxiv.org/abs/2406.03690v2
https://arxiv.org/pdf/2406.03690v2.pdf
https://github.com/toyotacrdl/ampic
true
true
false
none
https://paperswithcode.com/paper/identification-of-snps-in-genomes-using
GRAMEP: an alignment-free method based on the Maximum Entropy Principle for identifying SNPs
2405.01715
https://arxiv.org/abs/2405.01715v2
https://arxiv.org/pdf/2405.01715v2.pdf
https://github.com/omatheuspimenta/gramep
true
true
false
none
https://paperswithcode.com/paper/machine-learning-predictions-from
Machine learning predictions from unpredictable chaos
2503.14956
https://arxiv.org/abs/2503.14956v1
https://arxiv.org/pdf/2503.14956v1.pdf
https://github.com/kelu0124/TEPC
true
false
false
none
https://paperswithcode.com/paper/mistral-7b
Mistral 7B
2310.06825
https://arxiv.org/abs/2310.06825v1
https://arxiv.org/pdf/2310.06825v1.pdf
https://github.com/mgmalek/efficient_cross_entropy
false
false
true
pytorch
https://paperswithcode.com/paper/can-modifying-data-address-graph-domain
Can Modifying Data Address Graph Domain Adaptation?
2407.19311
https://arxiv.org/abs/2407.19311v1
https://arxiv.org/pdf/2407.19311v1.pdf
https://github.com/zjunet/GraphAlign
true
false
false
pytorch
https://paperswithcode.com/paper/attention-guided-cosine-margin-for-overcoming
Attention Guided Cosine Margin For Overcoming Class-Imbalance in Few-Shot Road Object Detection
2111.06639
https://arxiv.org/abs/2111.06639v1
https://arxiv.org/pdf/2111.06639v1.pdf
https://github.com/amajee11us/smile-fsod
false
false
true
pytorch
https://paperswithcode.com/paper/generating-realistic-3d-brain-mris-using-a
Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model
2212.08034
https://arxiv.org/abs/2212.08034v2
https://arxiv.org/pdf/2212.08034v2.pdf
https://github.com/jiaqiw01/MRIAnatEval
false
false
true
pytorch
https://paperswithcode.com/paper/large-scale-multi-domain-recommendation-an
Large-Scale Multi-Domain Recommendation: an Automatic Domain Feature Extraction and Personalized Integration Framework
2404.08361
https://arxiv.org/abs/2404.08361v2
https://arxiv.org/pdf/2404.08361v2.pdf
https://github.com/xidongbo/dfei
true
true
false
tf
https://paperswithcode.com/paper/fastspell-the-langid-magic-spell
FastSpell: the LangId Magic Spell
2404.08345
https://arxiv.org/abs/2404.08345v1
https://arxiv.org/pdf/2404.08345v1.pdf
https://github.com/mbanon/fastspell
true
true
false
none
https://paperswithcode.com/paper/a-classification-benchmark-for-artificial
A Classification Benchmark for Artificial Intelligence Detection of Laryngeal Cancer from Patient Voice
2412.16267
https://arxiv.org/abs/2412.16267v2
https://arxiv.org/pdf/2412.16267v2.pdf
https://github.com/mary-paterson/laryngealcancerclassificationbenchmark
true
true
false
none
https://paperswithcode.com/paper/instructpix2pix-learning-to-follow-image
InstructPix2Pix: Learning to Follow Image Editing Instructions
2211.09800
https://arxiv.org/abs/2211.09800v2
https://arxiv.org/pdf/2211.09800v2.pdf
https://github.com/lsl001006/zone
false
false
true
pytorch
https://paperswithcode.com/paper/zone-zero-shot-instruction-guided-local
ZONE: Zero-Shot Instruction-Guided Local Editing
2312.16794
https://arxiv.org/abs/2312.16794v2
https://arxiv.org/pdf/2312.16794v2.pdf
https://github.com/lsl001006/zone
true
true
true
pytorch
https://paperswithcode.com/paper/empowering-clinicians-and-democratizing-data
Large Language Models Streamline Automated Machine Learning for Clinical Studies
2308.14120
https://arxiv.org/abs/2308.14120v5
https://arxiv.org/pdf/2308.14120v5.pdf
https://github.com/tayebiarasteh/llmmed
true
true
true
none
https://paperswithcode.com/paper/a-benchmark-suite-for-systematically
A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts
2406.10368
https://arxiv.org/abs/2406.10368v2
https://arxiv.org/pdf/2406.10368v2.pdf
https://github.com/unitn-sml/rsbench-code
true
false
true
pytorch
https://paperswithcode.com/paper/autonomous-llm-driven-research-from-data-to
Autonomous LLM-driven research from data to human-verifiable research papers
2404.17605
https://arxiv.org/abs/2404.17605v1
https://arxiv.org/pdf/2404.17605v1.pdf
https://github.com/technion-kishony-lab/data-to-paper
true
true
true
none
https://paperswithcode.com/paper/deslib-a-dynamic-ensemble-selection-library
DESlib: A Dynamic ensemble selection library in Python
1802.04967
http://arxiv.org/abs/1802.04967v3
http://arxiv.org/pdf/1802.04967v3.pdf
https://github.com/scikit-learn-contrib/DESlib
true
true
true
none
https://paperswithcode.com/paper/an-open-world-lottery-ticket-for-out-of
The Open-World Lottery Ticket Hypothesis for OOD Intent Classification
2210.07071
https://arxiv.org/abs/2210.07071v3
https://arxiv.org/pdf/2210.07071v3.pdf
https://github.com/zyh190507/open-world-lottery
true
true
false
pytorch
https://paperswithcode.com/paper/factuality-enhanced-language-models-for-open
Factuality Enhanced Language Models for Open-Ended Text Generation
2206.04624
https://arxiv.org/abs/2206.04624v3
https://arxiv.org/pdf/2206.04624v3.pdf
https://github.com/ranggihwang/pregated_moe
false
false
true
pytorch
https://paperswithcode.com/paper/global-local-collaborative-inference-with-llm
Global-Local Collaborative Inference with LLM for Lidar-Based Open-Vocabulary Detection
2407.08931
https://arxiv.org/abs/2407.08931v1
https://arxiv.org/pdf/2407.08931v1.pdf
https://github.com/gradiustwinbee/glis
true
true
false
none
https://paperswithcode.com/paper/elucidating-the-theoretical-underpinnings-of
Elucidating the theoretical underpinnings of surrogate gradient learning in spiking neural networks
2404.14964
https://arxiv.org/abs/2404.14964v3
https://arxiv.org/pdf/2404.14964v3.pdf
https://github.com/fmi-basel/surrogate-gradient-theory
true
true
true
jax
https://paperswithcode.com/paper/astropop-the-astronomical-polarimetry-and
ASTROPOP: the ASTROnomical POlarimetry and Photometry pipeline
1811.01408
https://arxiv.org/abs/1811.01408v1
https://arxiv.org/pdf/1811.01408v1.pdf
https://github.com/juliotux/astropop
true
true
true
none
https://paperswithcode.com/paper/deep-learning-in-medical-image-registration-1
Deep Learning in Medical Image Registration: Magic or Mirage?
2408.05839
https://arxiv.org/abs/2408.05839v2
https://arxiv.org/pdf/2408.05839v2.pdf
https://github.com/rohitrango/Magic-or-Mirage
true
false
false
pytorch