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representation learning

6174 papers

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Also known as

WAV2VEC2.0 RL NRMS NDFS

Co-occurring keywords

contrastive learning (3979) self-supervised learning (3751) transfer learning (5442) neural network (6616) unsupervised learning (3255) graph neural network (3945) multimodal learning (4622) domain adaptation (4578) feature learning (1309) language model (4573)

Papers

BASiS: Batch Aligned Spectral Embedding Space CVPR 2023
Enhanced Multimodal Representation Learning With Cross-Modal KD CVPR 2023
Sample-Specific Debiasing for Better Image-Text Models MLHC 2023
Public Opinion Field Effect Fusion in Representation Learning for Trending Topics Diffusion NIPS 2023
PlanE: Representation Learning over Planar Graphs NIPS 2023
A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking NIPS 2023
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning NIPS 2023
A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs NIPS 2023
No Representation Rules Them All in Category Discovery NIPS 2023
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells NIPS 2023
Learning Large Graph Property Prediction via Graph Segment Training NIPS 2023
Labeling Neural Representations with Inverse Recognition NIPS 2023
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation NIPS 2023
Relax, it doesn’t matter how you get there: A new self-supervised approach for multi-timescale behavior analysis NIPS 2023
Generalised f-Mean Aggregation for Graph Neural Networks NIPS 2023
Concept Algebra for (Score-Based) Text-Controlled Generative Models NIPS 2023
Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning NIPS 2023
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem NIPS 2023
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning NIPS 2023
Disentanglement via Latent Quantization NIPS 2023
Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First NIPS 2023
Geodesic Multi-Modal Mixup for Robust Fine-Tuning NIPS 2023
Generalized Information-theoretic Multi-view Clustering NIPS 2023
Understanding and Improving Feature Learning for Out-of-Distribution Generalization NIPS 2023
Subclass-Dominant Label Noise: A Counterexample for the Success of Early Stopping NIPS 2023