RoyRin / arxiv_connectionsLinks
interactively identify related Authors on arxiv
☆13Updated last year
Alternatives and similar repositories for arxiv_connections
Users that are interested in arxiv_connections are comparing it to the libraries listed below
Sorting:
- Official repository for CMU Machine Learning Department's 10721: "Philosophical Foundations of Machine Intelligence".☆262Updated 2 years ago
- A library for bridging Python and HTML/Javascript (via Svelte) for creating interactive visualizations☆192Updated 3 years ago
- LipSDP - Lipschitz Estimation for Neural Networks☆69Updated 3 years ago
- Hessian spectral density estimation in TF and Jax☆123Updated 4 years ago
- Influence Functions with (Eigenvalue-corrected) Kronecker-Factored Approximate Curvature☆156Updated 3 weeks ago
- ☆273Updated last year
- Tools for studying developmental interpretability in neural networks.☆99Updated 3 weeks ago
- ☆122Updated last year
- Redwood Research's transformer interpretability tools☆14Updated 3 years ago
- Psych-GA.2207 Categories and Concepts☆16Updated last year
- Einsum with einops style variable names☆16Updated last year
- 🧀 Pytorch code for the Fromage optimiser.☆125Updated last year
- Official repository for CMU Machine Learning Department's 10717: "The Art of the Paper".☆288Updated 3 years ago
- Notebooks accompanying Anthropic's "Toy Models of Superposition" paper☆127Updated 2 years ago
- 🧠 Starter templates for doing interpretability research☆72Updated 2 years ago
- Discount jupyter.☆51Updated 4 months ago
- Parameter-Free Optimizers for Pytorch☆130Updated last year
- Algorithms for Privacy-Preserving Machine Learning in JAX☆95Updated this week
- ☆208Updated 2 years ago
- ☆62Updated 4 years ago
- NeuroSurgeon is a package that enables researchers to uncover and manipulate subnetworks within models in Huggingface Transformers☆41Updated 5 months ago
- Mechanistic Interpretability for Transformer Models☆51Updated 3 years ago
- Mechanistic Interpretability Visualizations using React☆262Updated 6 months ago
- The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)☆41Updated last year
- Datasets derived from US census data☆265Updated last year
- Erasing concepts from neural representations with provable guarantees☆230Updated 5 months ago
- ☆231Updated 9 months ago
- Jiminy Cricket Environment (NeurIPS 2021)☆25Updated 3 years ago
- ☆157Updated 3 years ago
- A TinyStories LM with SAEs and transcoders☆12Updated 3 months ago