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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
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Papers (including subtopics)

Digital Scale: Open-Source On-Device BMI Estimation from Smartphone Camera Images Trained on a Large-Scale Real-World Dataset AAAI 2026 DiLO: Disentangled Latent Optimization for Learning Shape and Deformation in Grouped Deforming 3D Objects AAAI 2026 Dimension Reduction via Sum-of-Squares and Improved Clustering Algorithms for Non-Spherical Mixtures COLT 2026 DIN: Dual Impulse Network for Multi-view Representation Learning AAAI 2026 DIRECT: Directional Relevance in Conversational Trajectories EACL 2026 Directed Attention is All You Need: Profiling Style from Limited Text Data EACL 2026 DiRe: Diversity-promoting Regularization for Dataset Condensation WACV 2026 Discovering Decoupled Functional Modules in Large Language Models AAAI 2026 Discovering Hybrid World Representations with Co-Evolving Foundation Models AAAI 2026 Discriminative Graph Embedding Framework via Label-Free Marginal Fisher Analysis AAAI 2026 Disentangled Hypergraph-Guided Mamba Scanning for Fine-Grained Visual Recognition AAAI 2026 Disentangling for Transfer: Boosting Limited Modalities via Information-Theoretic Regularization and Cross-Modal Reconstruction AAAI 2026 DisGraph-RP: Graph-Augmented Temporal Modeling with Aspect-Based Contrastive Encoding of Discharge Summary for Readmission Prediction EACL 2026 Distribution Highlighted Reference-based Label Distribution Learning for Facial Age Estimation WACV 2026 Diversity Preserving Coresets for Image Quality Assessment WACV 2026 Diversity Recommendation via Causal Deconfounding of Co-purchase Relations and Counterfactual Exposure AAAI 2026 DMCAR: Disentangled Mixture-of-Experts with Context-Aware Routing for Multi-View Clustering AAAI 2026 Do Large Language Models Think like the Brain? Sentence-Level Evidences from Layer-Wise Embeddings and fMRI AAAI 2026 Domain-Aware Multi-View Contrastive Representation Learning for Protein Subcellular Localization Prediction AAAI 2026 Domain-Skewed Federated Learning with Feature Decoupling and Calibration CVPR 2026 Don’t Generate, Classify! Low-Latency Prompt Optimization with Structured Complementary Prompt EACL 2026 Don’t Test What You Can Deduce: Causal Discovery with Logical Inference UAI 2026 Do Retrieval Augmented Language Models Know When They Don’t Know? AAAI 2026 DOTGraph: CLIP-Driven Feature Disentanglement and Optimal Transport based Graph Learning for Few-Shot Segmentation WACV 2026 Do We Truly Need So Many Samples? Multi-LLM Repeated Sampling Efficiently Scales Test-Time Compute AAAI 2026