Research map / Probabilistic and scientific modeling / Dynamical systems
Disentanglement with Biological Constraints: A Theory of Functional Cell Types
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
- Disentangling Representations through Multi-task Learning (ICLR 2025 · similarity 0.89)
- Range, not Independence, Drives Modularity in Biologically Inspired Representations (ICLR 2025 · similarity 0.86)
- Wasserstein Distances, Neuronal Entanglement, and Sparsity (ICLR 2025 · similarity 0.85)
- Biologically Plausible Brain Graph Transformer (ICLR 2025 · similarity 0.85)
- Flexible task abstractions emerge in linear networks with fast and bounded units (NeurIPS 2024 · similarity 0.85)
- Scaling Laws and Tradeoffs in Recurrent Networks of Expressive Neurons (NeurIPS 2026 · similarity 0.84)
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.
