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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
51
357
966
4,853
5,823
2000
'5
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'15
'20
'25

Papers (including subtopics)

Learning Optimal Features via Partial Invariance AAAI 2023 Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments JMLR 2023 Learning Partial Correlation Based Deep Visual Representation for Image Classification CVPR 2023 Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces JMLR 2023 Learning Polysemantic Spoof Trace: A Multi-Modal Disentanglement Network for Face Anti-spoofing AAAI 2023 Learning Preconditioners for Conjugate Gradient PDE Solvers ICML 2023 Learning Preference Models with Sparse Interactions of Criteria IJCAI 2023 Learning Prescriptive ReLU Networks ICML 2023 Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance NeurIPS 2023 Learning Probabilistic Topological Representations Using Discrete Morse Theory ICLR 2023 Learning Prototype Classifiers for Long-Tailed Recognition IJCAI 2023 Learning Query Adaptive Anchor Representation for Inductive Relation Prediction ACL 2023 Learning Rain Location Prior for Nighttime Deraining ICCV 2023 Learning Rate Schedules in the Presence of Distribution Shift ICML 2023 Learning Relational Causal Models with Cycles through Relational Acyclification AAAI 2023 Learning Reliable Logical Rules with SATNet NeurIPS 2023 Learning Repeatable Speech Embeddings Using An Intra-class Correlation Regularizer NeurIPS 2023 Learning Representations of Bi-level Knowledge Graphs for Reasoning beyond Link Prediction AAAI 2023 Learning Representations without Compositional Assumptions ICML 2023 Learning robust representation for reinforcement learning with distractions by reward sequence prediction UAI 2023 Learning Robust State Observers using Neural ODEs L4DC 2023 Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction NeurIPS 2023 Learning Sample Relationship for Exposure Correction CVPR 2023 Learning Second-Order Attentive Context for Efficient Correspondence Pruning AAAI 2023 Learning Semantic-Aware Disentangled Representation for Flexible 3D Human Body Editing CVPR 2023