allenbai01 / transformers-as-statisticiansLinks
☆34Updated 2 years ago
Alternatives and similar repositories for transformers-as-statisticians
Users that are interested in transformers-as-statisticians are comparing it to the libraries listed below
Sorting:
- ☆71Updated 11 months ago
- Official repository for our paper, Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Mode…☆19Updated 11 months ago
- ☆18Updated last year
- Code for the paper "Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression"☆23Updated 2 years ago
- Code for testing DCT plus Sparse (DCTpS) networks☆14Updated 4 years ago
- Code and data for the paper "Understanding Hidden Context in Preference Learning: Consequences for RLHF"☆32Updated last year
- ☆241Updated last year
- Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implici…☆106Updated 2 years ago
- Bayesian Low-Rank Adaptation for Large Language Models☆36Updated last year
- Code for Paper (Policy Optimization in RLHF: The Impact of Out-of-preference Data)☆28Updated last year
- Rewarded soups official implementation☆62Updated 2 years ago
- Provably (and non-vacuously) bounding test error of deep neural networks under distribution shift with unlabeled test data.☆10Updated last year
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated 2 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆36Updated 3 years ago
- The official repository for our paper "Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks". We…☆46Updated 2 years ago
- ☆19Updated last year
- Code for "The Expressive Power of Low-Rank Adaptation".☆20Updated last year
- Preprint: Asymmetry in Low-Rank Adapters of Foundation Models☆35Updated last year
- This is an official repository for "LAVA: Data Valuation without Pre-Specified Learning Algorithms" (ICLR2023).☆51Updated last year
- ☆31Updated 7 months ago
- Gradient Estimation with Discrete Stein Operators (NeurIPS 2022)☆17Updated 2 years ago
- This repository includes code to reproduce the tables in "Loss Landscapes are All You Need: Neural Network Generalization Can Be Explaine…☆40Updated 2 years ago
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆16Updated 3 years ago
- ☆27Updated 2 years ago
- ☆31Updated last year
- Revisiting Efficient Training Algorithms For Transformer-based Language Models (NeurIPS 2023)☆80Updated 2 years ago
- Code for our paper "Generative Flow Networks for Discrete Probabilistic Modeling"☆84Updated 2 years ago
- [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…☆14Updated 3 years ago
- ☆33Updated last year
- [NeurIPS 2021] A Geometric Analysis of Neural Collapse with Unconstrained Features☆59Updated 3 years ago