Representation Learning

On Non-Linear operators for Geometric Deep Learning NeurIPS 2022 On PAC-Bayesian reconstruction guarantees for VAEs AISTATS 2022 On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation COLING 2022 On the Curious Case of l2 norm of Sense Embeddings EMNLP 2022 On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs NeurIPS 2022 On the Effect of Isotropy on VAE Representations of Text ACL 2022 On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement Learning NeurIPS 2022 On the Equivalence Between Temporal and Static Equivariant Graph Representations ICML 2022 On the equivalence of Oja’s algorithm and GROUSE AISTATS 2022 On the expressivity of bi-Lipschitz normalizing flows ACML 2022 On-the-fly ASR Corrections with Audio Exemplars Interspeech 2022 On the Generalization of Representations in Reinforcement Learning AISTATS 2022 On the Geometry of Concreteness ACL 2022 On the Identifiability of Nonlinear ICA: Sparsity and Beyond NeurIPS 2022 On the Importance of Asymmetry for Siamese Representation Learning CVPR 2022 On the Integration of Self-Attention and Convolution CVPR 2022 On the Interplay between Information Loss and Operation Loss in Representations for Classification AISTATS 2022 On the Limits of Evaluating Embodied Agent Model Generalization Using Validation Sets ACL 2022 On the Representation Collapse of Sparse Mixture of Experts NeurIPS 2022 On the Robustness of Reading Comprehension Models to Entity Renaming NAACL 2022 On the Role of Spatial, Spectral, and Temporal Processing for DNN-based Non-linear Multi-channel Speech Enhancement Interspeech 2022 On the Strong Correlation Between Model Invariance and Generalization NeurIPS 2022 On the Surrogate Gap between Contrastive and Supervised Losses ICML 2022 On the Symmetries of Deep Learning Models and their Internal Representations NeurIPS 2022 On the Transformation of Latent Space in Fine-Tuned NLP Models EMNLP 2022