gladia-research-group / explanatory-learningLinks
This is the official repository for "Explanatory Learning: Beyond Empiricism in Neural Networks".
☆14Updated 3 years ago
Alternatives and similar repositories for explanatory-learning
Users that are interested in explanatory-learning are comparing it to the libraries listed below
Sorting:
- A Python package for analyzing and transforming neural latent spaces.☆52Updated 3 months ago
- Neural Networks and the Chomsky Hierarchy☆210Updated last year
- Mechanistic Interpretability for Transformer Models☆53Updated 3 years ago
- Erasing concepts from neural representations with provable guarantees☆238Updated 9 months ago
- How to Turn Your Knowledge Graph Embeddings into Generative Models☆53Updated last year
- Notebooks accompanying Anthropic's "Toy Models of Superposition" paper☆129Updated 3 years ago
- Probabilistic programming with large language models☆141Updated 3 months ago
- A domain-specific probabilistic programming language for modeling and inference with language models☆136Updated 6 months ago
- Brain-Inspired Modular Training (BIMT), a method for making neural networks more modular and interpretable.☆173Updated 2 years ago
- ☆279Updated last year
- Flexible library for merging large language models (LLMs) via evolutionary optimization (ACL 2025 Demo).☆90Updated 2 months ago
- Language-annotated Abstraction and Reasoning Corpus☆93Updated 2 years ago
- ☆27Updated 2 years ago
- Code Release for "Broken Neural Scaling Laws" (BNSL) paper☆59Updated last year
- 🧠 Starter templates for doing interpretability research☆74Updated 2 years ago
- Attribution-based Parameter Decomposition☆31Updated 4 months ago
- Codebase for VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming☆21Updated 2 years ago
- Library that contains implementations of machine learning components in the hyperbolic space☆142Updated last year
- An interpreter for RASP as described in the ICML 2021 paper "Thinking Like Transformers"☆320Updated last year
- ☆110Updated 8 months ago
- Keeping language models honest by directly eliciting knowledge encoded in their activations.☆211Updated this week
- Tools for studying developmental interpretability in neural networks.☆111Updated 4 months ago
- ☆128Updated 2 years ago
- ☆107Updated 8 months ago
- ☆74Updated 2 weeks ago
- See the issue board for the current status of active and prospective projects!☆65Updated 3 years ago
- Personal implementation of ASIF by Antonio Norelli☆26Updated last year
- ☆247Updated last year
- Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scale, TACL (2022)☆130Updated 4 months ago
- The Happy Faces Benchmark☆15Updated 2 years ago