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Learning Types

32,670 papers (1 classified directly here)

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

Representation Learning (5,307) Multimodal Learning (3,969) Self-Supervised Learning (3,492) Transfer Learning (2,890) Adversarial Learning (2,199) Deep Learning (1,883) Contrastive Learning (1,730) Reinforcement Learning (1,500) Knowledge Distillation (1,494) Fine-Tuning (1,117) Multi-Task Learning (1,069) Domain Adaptation (977) Zero-Shot Learning (758) Unsupervised Learning (734) Few-Shot Learning (694) Classification (621) Retrieval-Augmented Generation (606) Data Augmentation (583) Semi-Supervised Learning (450) Weakly Supervised Learning (429) Continual Learning (408) In-Context Learning (387) Sequence Modeling (375) Meta-Learning (252) Metric Learning (232) Ensemble Learning (223) Federated Learning (215) Multi-Lingual Learning (199) Robustness (197) Parameter-Efficient Fine-Tuning (190) Imitation Learning (180) Prompt Engineering (170) Chain-of-Thought Reasoning (153) Curriculum Learning (146) Synthetic Data Generation (143) Reinforcement Learning from Human Feedback (141) Multi-Label Classification (123) Regression (117) Generative Model (109) Semantic Segmentation (106) Domain Generalization (105) Uncertainty Quantification (98) Controllable Generation (93) Text Generation (86) Neural Architecture Search (80) Object Detection (80) Image Generation (79) Multi-Agent Systems (76) Feature Learning (74) Preference Learning (73) Machine Translation (71) Out-of-Distribution Detection (68) Machine Unlearning (63) Generation (61) Reasoning (54) Multi-View Learning (53) Time Series (52) Instruction Tuning (50) Distributed Learning (50) Image Restoration (49) Chain-of-Thought (48) Active Learning (47) Text Classification (43) Distribution Shift (43) Structured Prediction (42) Clustering (41) Image Classification (40) Model Merging (37) Sparse Learning (36) Sequence Labeling (36) Multi-Instance Learning (35) Anomaly Detection (33) Image Processing (33) Code Generation (31) Fairness (30) Robust Learning (28) Multi-Domain Learning (27) Supervised Learning (26) Model-Based RL (25) Natural Language Generation (24) Privacy (21) Multi-Objective Optimization (19) Multi-Scale Learning (19) Neural Machine Translation (18) Causal Inference (14) Instance Segmentation (9) Interactive Learning (9) Multi-Label Learning (9) Multi-Source Learning (9) Multi-Class Classification (8)

Papers per year

38
179
3,018
5,737
'10
'15
'20
'25

Papers (including subtopics)

Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching ICML 2016 Fast Training of Triplet-Based Deep Binary Embedding Networks CVPR 2016 Fine-Grained Categorization and Dataset Bootstrapping Using Deep Metric Learning With Humans in the Loop CVPR 2016 From Keyframes to Key Objects: Video Summarization by Representative Object Proposal Selection CVPR 2016 GAKE: Graph Aware Knowledge Embedding COLING 2016 Gaussian Conditional Random Field Network for Semantic Segmentation CVPR 2016 Generating Images with Perceptual Similarity Metrics based on Deep Networks NeurIPS 2016 Generating Long-term Trajectories Using Deep Hierarchical Networks NeurIPS 2016 Generating Natural Video Descriptions via Multimodal Processing Interspeech 2016 Generating Video Description using Sequence-to-sequence Model with Temporal Attention COLING 2016 Generative Adversarial Text to Image Synthesis ICML 2016 Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data NeurIPS 2016 Harnessing Object and Scene Semantics for Large-Scale Video Understanding CVPR 2016 Hashtag Recommendation with Topical Attention-Based LSTM COLING 2016 Hedged Deep Tracking CVPR 2016 Hierarchically Gated Deep Networks for Semantic Segmentation CVPR 2016 Hierarchical Recurrent Neural Encoder for Video Representation With Application to Captioning CVPR 2016 Highlight Detection With Pairwise Deep Ranking for First-Person Video Summarization CVPR 2016 Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Learn Neural Networks JMLR 2016 iLab-20M: A Large-Scale Controlled Object Dataset to Investigate Deep Learning CVPR 2016 Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections NeurIPS 2016 Improved Deep Metric Learning with Multi-class N-pair Loss Objective NeurIPS 2016 Improved MVDR Beamforming Using Single-Channel Mask Prediction Networks Interspeech 2016 Improved Techniques for Training GANs NeurIPS 2016 Improving Deep Neural Networks Based Speaker Verification Using Unlabeled Data Interspeech 2016