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Learning Types

56,253 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Self-Supervised Learning (8,965) Adversarial Learning (5,204) Unsupervised Learning (4,874) Transfer Learning (4,808) Weakly Supervised Learning (3,938) Contrastive Learning (3,748) Zero-Shot Learning (3,130) Semi-Supervised Learning (3,128) Reinforcement Learning (3,118) Multi-Task Learning (2,556) Evaluation (2,164) Continual Learning (2,107) Active Learning (1,983) Few-Shot Learning (1,840) Deep Learning (1,404) Online Learning (1,360) Multi-Armed Bandits (1,327) Multimodal Learning (1,289) Supervised Learning (986) Multi-Agent Systems (813) Uncertainty Quantification (805) Causal Inference (636) Robustness (576) Retrieval-Augmented Generation (565) Fine-Tuning (490) Ensemble Learning (482) In-Context Learning (439) Multi-Label Classification (430) Imitation Learning (387) Prompt Engineering (270) Multi-Lingual Learning (269) Distribution Shift (264) Reinforcement Learning from Human Feedback (209) Regularization (207) Exploration-Exploitation (203) Generative Models (200) Multi-Objective Optimization (185) Out-of-Distribution Detection (176) Sparse Learning (165) Sampling (150) Preference Learning (136) Offline Reinforcement Learning (130) Multi-Label Learning (128) Markov Decision Process (127) Neural Architecture Search (122) Multi-Instance Learning (121) Multi-View Learning (117) Robust Learning (110) Generative Model (110) Time Series (108) Large Language Models (104) Exploration (103) Hyperparameter Optimization (99) Machine Unlearning (95) Imbalanced Learning (93) Machine Translation (93) Multi-Class Classification (85) Differential Privacy (82) Time Series Analysis (71) Reasoning (70) Calibration (67) Structure Learning (66) Physics-Informed Learning (62) Class Imbalance (58) Model-Based RL (55) Interactive Learning (55) Multi-Domain Learning (47) Inverse Reinforcement Learning (46) Crowdsourcing (40) Off-Policy Learning (38) Label Noise (38) Noisy Label Learning (35) Offline RL (32) Attention (32) Evolutionary Algorithm (32) Decision Making (31) Policy Learning (30) Personalization (28) Low-Resource Learning (26) Collaborative Filtering (25) Self-Training (24) Sequential Modeling (24) Parameter Estimation (23) Survival Analysis (21) Machine Learning (20) Parameter-Efficient Fine-Tuning (20) Synthetic Data Generation (20) Annotation (18) Symbolic Regression (18) AutoML (16) Security (15) Multi-Source Learning (13) Distant Supervision (13) Text Generation (11) Distributional Reinforcement Learning (9) Sentiment Analysis (9) Multi-Hop Reasoning (9) Language Modeling (9) Code Generation (8) Multi-Object Tracking (8) Natural Language Inference (7) Chain-of-Thought (6) Question Answering (5)

Papers per year

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20
220
477
4,652
9,258
2000
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Papers (including subtopics)

Uncertainty-Aware Curriculum Learning for Neural Machine Translation ACL 2020 Uncertainty-Aware Deep Classifiers Using Generative Models AAAI 2020 Uncertainty Aware Graph Gaussian Process for Semi-Supervised Learning AAAI 2020 Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation NeurIPS 2020 Uncertainty-Aware Score Distribution Learning for Action Quality Assessment CVPR 2020 Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization AAAI 2020 Uncertainty-aware Self-training for Few-shot Text Classification NeurIPS 2020 Uncertainty-Aware Semantic Augmentation for Neural Machine Translation EMNLP 2020 Uncertainty Aware Semi-Supervised Learning on Graph Data NeurIPS 2020 Uncertainty Based Camera Model Selection CVPR 2020 Uncertainty Estimation Using a Single Deep Deterministic Neural Network ICML 2020 Uncertainty-guided Continual Learning with Bayesian Neural Networks ICLR 2020 Uncertainty in Neural Networks: Approximately Bayesian Ensembling AISTATS 2020 Uncertainty Modeling for Machine Comprehension Systems using Efficient Bayesian Neural Networks COLING 2020 Uncertainty over Uncertainty: Investigating the Assumptions, Annotations, and Text Measurements of Economic Policy Uncertainty EMNLP 2020 Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery AISTATS 2020 Uncertainty Quantification for Inferring Hawkes Networks NeurIPS 2020 Uncorrected Least-Squares Temporal Difference with Lambda-Return AAAI 2020 Undersensitivity in Neural Reading Comprehension EMNLP 2020 Understanding Adversarial Examples From the Mutual Influence of Images and Perturbations CVPR 2020 Understanding and Exploring the Network with Stochastic Architectures NeurIPS 2020 Understanding and Improving Fast Adversarial Training NeurIPS 2020 Understanding and Improving Information Transfer in Multi-Task Learning ICLR 2020 Understanding and Mitigating the Tradeoff between Robustness and Accuracy ICML 2020 Understanding and Robustifying Differentiable Architecture Search ICLR 2020