Representation Learning

Decoupling-and-Aggregating for Image Exposure Correction CVPR 2023 Decoupling Learning and Remembering: A Bilevel Memory Framework With Knowledge Projection for Task-Incremental Learning CVPR 2023 Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery ACL 2023 Deep Attentive Model for Knowledge Tracing AAAI 2023 Deep Deterministic Uncertainty: A New Simple Baseline CVPR 2023 Deep Discriminative Spatial and Temporal Network for Efficient Video Deblurring CVPR 2023 Deep Ensembles for Graphs with Higher-order Dependencies ICLR 2023 Deep equilibrium models as estimators for continuous latent variables AISTATS 2023 Deep Factorized Metric Learning CVPR 2023 Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search ICML 2023 Deep Graph Representation Learning and Optimization for Influence Maximization ICML 2023 Deep Graph Structural Infomax AAAI 2023 Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models AISTATS 2023 Deep Hashing-based Dynamic Stock Correlation Estimation via Normalizing Flow IJCAI 2023 Deep Hierarchical Communication Graph in Multi-Agent Reinforcement Learning IJCAI 2023 Deep Joint Source-Channel Coding with Iterative Source Error Correction AISTATS 2023 Deep Kernel Regression with Finite Learnable Kernels ACML 2023 Deep Learning on Implicit Neural Representations of Shapes ICLR 2023 Deep learning with kernels through RKHM and the Perron-Frobenius operator NeurIPS 2023 Deep Multitask Learning with Progressive Parameter Sharing ICCV 2023 Deep Non-line-of-sight Imaging from Under-scanning Measurements NeurIPS 2023 Deep Polarization Reconstruction With PDAVIS Events CVPR 2023 Deep Representation Learning for Prediction of Temporal Event Sets in the Continuous Time Domain ACML 2023 Deep Span Representations for Named Entity Recognition ACL 2023 Deep Stochastic Processes via Functional Markov Transition Operators NeurIPS 2023