Research map / Label-efficient and robust learning / Recognition and long-tail
The HSIC Bottleneck: Deep Learning without Back-Propagation
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression (ICLR 2024 · similarity 0.84)
- Towards Continual Learning Desiderata via HSIC-Bottleneck Orthogonalization and Equiangular Embedding (AAAI 2024 · similarity 0.83)
- Scaling Down Deep Learning with MNIST-1D (ICML 2024 · similarity 0.83)
- A Rate-Distortion View of Uncertainty Quantification (ICML 2024 · similarity 0.82)
- One-Time Soft Alignment Enables Resilient Learning without Weight Transport (NeurIPS 2026 · similarity 0.82)
- Understanding and Leveraging the Learning Phases of Neural Networks (AAAI 2024 · similarity 0.82)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
