Representation Learning

Learning Semantic Representations to Verify Hardware Designs NeurIPS 2021 Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases AAAI 2021 Learning Shape Representations for Person Re-Identification Under Clothing Change WACV 2021 Learning Shared Subgraphs in Ising Model Pairs AISTATS 2021 Learning Signal-Agnostic Manifolds of Neural Fields NeurIPS 2021 Learning Smooth and Fair Representations AISTATS 2021 Learning Sparse Sentence Encoding without Supervision: An Exploration of Sparsity in Variational Autoencoders ACL 2021 Learning Speech Structure to Improve Time-Frequency Masks Interspeech 2021 Learning State Representations from Random Deep Action-conditional Predictions NeurIPS 2021 Learning Statistical Texture for Semantic Segmentation CVPR 2021 Learning Stochastic Equivalence based on Discrete Ricci Curvature IJCAI 2021 Learning Strategies in Decentralized Matching Markets under Uncertain Preferences JMLR 2021 Learning Syntactic Dense Embedding with Correlation Graph for Automatic Readability Assessment ACL 2021 Learning Target Candidate Association To Keep Track of What Not To Track ICCV 2021 Learning Task-General Representations with Generative Neuro-Symbolic Modeling ICLR 2021 Learning Task Informed Abstractions ICML 2021 Learning Tensor Low-Rank Prior for Hyperspectral Image Reconstruction CVPR 2021 Learning Term Embeddings for Lexical Taxonomies AAAI 2021 Learning the Latent Heat Diffusion Process through Structural Brain Network from Longitudinal β-Amyloid Data MIDL 2021 Learning the Predictability of the Future CVPR 2021 Learning To Aggregate and Personalize 3D Face From In-the-Wild Photo Collection CVPR 2021 Learning to Assimilate in Chaotic Dynamical Systems NeurIPS 2021 Learning to Compose Visual Relations NeurIPS 2021 Learning to Decompose and Organize Complex Tasks NAACL 2021 Learning to Ground Multi-Agent Communication with Autoencoders NeurIPS 2021