Core Methods
51,083 papers (8 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Representation Learning (22,308)
Classification (15,497)
Regression (5,281)
Clustering (3,809)
Embedding Learning (3,795)
Metric Learning (2,938)
Graph Neural Networks (1,211)
Graphical Models (1,093)
Feature Learning (891)
Kernel Methods (795)
Dimensionality Reduction (780)
Interpretability (512)
Feature Selection (511)
Matrix Factorization (408)
Ranking (315)
Ensemble Methods (300)
Support Vector Machine (295)
Anomaly Detection (281)
Sequence Modeling (244)
Structured Prediction (237)
Sequence Labeling (157)
Topic Modeling (150)
Sparse Coding (140)
Matrix Completion (131)
Neural Networks (114)
Retrieval (105)
Density Estimation (104)
Estimation (83)
Inference (56)
Decision Tree (50)
Feature Extraction (40)
Model Selection (39)
Prediction (35)
Information Extraction (7)
Papers per year
4
21
30
55
40
51
225
219
249
257
357
364
480
942
818
966
1,394
2,092
3,114
4,415
4,853
5,064
5,371
5,992
6,412
5,823
1,475
2000
'5
'10
'15
'20
'25
Papers (including subtopics)
On the Effectiveness of Supervision in Asymmetric Non-Contrastive Learning
ICML 2024
On the Efficiency of ERM in Feature Learning
NeurIPS 2024
On the Estimation of Image-matching Uncertainty in Visual Place Recognition
CVPR 2024
On the estimation of persistence intensity functions and linear representations of persistence diagrams
AISTATS 2024
On the Expressive Power of Spectral Invariant Graph Neural Networks
ICML 2024
On the Expressive Power of Tree-Structured Probabilistic Circuits
NeurIPS 2024
On the Faithfulness of Vision Transformer Explanations
CVPR 2024
On the Generalization of Training-based ChatGPT Detection Methods
EMNLP 2024
On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution
NeurIPS 2024
On the Identifiability of Quantized Factors
CLeaR 2024
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
NeurIPS 2024
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
JMLR 2024
On the impact of several regularization techniques on label noise robustness of self-supervised speaker verification systems
Interspeech 2024
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory
NeurIPS 2024
On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods
AAAI 2024
On the Intrinsic Structures of Spiking Neural Networks
JMLR 2024
On the Joint Interaction of Models, Data, and Features
ICLR 2024
On the Language Encoder of Contrastive Cross-modal Models
ACL 2024
On the Lasso for Graphical Continuous Lyapunov Models
CLeaR 2024
On the Learnability of Out-of-distribution Detection
JMLR 2024
On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice
NeurIPS 2024
On the Misspecification of Linear Assumptions in Synthetic Controls
AISTATS 2024
On the Multilingual Ability of Decoder-based Pre-trained Language Models: Finding and Controlling Language-Specific Neurons
NAACL 2024
On the Nonlinearity of Layer Normalization
ICML 2024
On the Nyström Approximation for Preconditioning in Kernel Machines
AISTATS 2024