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Representation Learning

4,925 papers

Papers per year

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Papers

Robust Disentanglement of a Few Factors at a Time using rPU-VAE NIPS 2020
CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations NIPS 2020
A Discrete Variational Recurrent Topic Model without the Reparametrization Trick NIPS 2020
Efficient Generation of Structured Objects with Constrained Adversarial Networks NIPS 2020
The Autoencoding Variational Autoencoder NIPS 2020
COBE: Contextualized Object Embeddings from Narrated Instructional Video NIPS 2020
Supermasks in Superposition NIPS 2020
Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation NIPS 2020
Parametric Instance Classification for Unsupervised Visual Feature learning NIPS 2020
Learning efficient task-dependent representations with synaptic plasticity NIPS 2020
Bayesian Attention Modules NIPS 2020
Explicit Regularisation in Gaussian Noise Injections NIPS 2020
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning NIPS 2020
Functional Regularization for Representation Learning: A Unified Theoretical Perspective NIPS 2020
The Dilemma of TriHard Loss and an Element-Weighted TriHard Loss for Person Re-Identification NIPS 2020
Disentangling by Subspace Diffusion NIPS 2020
Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies NIPS 2020
Representation Learning for Integrating Multi-domain Outcomes to Optimize Individualized Treatment NIPS 2020
Inverse Learning of Symmetries NIPS 2020
Regularizing Towards Permutation Invariance In Recurrent Models NIPS 2020
Supervised Contrastive Learning NIPS 2020
Learning Optimal Representations with the Decodable Information Bottleneck NIPS 2020
Weak Form Generalized Hamiltonian Learning NIPS 2020
CircleGAN: Generative Adversarial Learning across Spherical Circles NIPS 2020
Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning NIPS 2020