dobriban / Principles-of-AI-LLMsLinks
Materials for the course Principles of AI: LLMs at UPenn (Stat 9911, Spring 2025). LLM architectures, training paradigms (pre- and post-training, alignment), test-time computation, reasoning, safety and robustness (jailbreaking, oversight, uncertainty), representations, interpretability (circuits), etc.
☆37Updated last month
Alternatives and similar repositories for Principles-of-AI-LLMs
Users that are interested in Principles-of-AI-LLMs are comparing it to the libraries listed below
Sorting:
- Resources for education in statistics and machine learning: from advanced undergraduate to research level☆93Updated last year
- A package for conformal prediction with conditional guarantees.☆60Updated 4 months ago
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆173Updated last year
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆44Updated last year
- ☆187Updated 2 years ago
- Extending Conformal Prediction to LLMs☆67Updated last year
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆99Updated 5 months ago
- ☆60Updated 3 months ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆67Updated 7 months ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆66Updated 5 months ago
- Course materials for Advanced Topics in Statistical Learning, Spring 2024☆22Updated last month
- ☆34Updated last month
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆67Updated 2 years ago
- Tabular In-Context Learning☆78Updated 4 months ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆84Updated last year
- Experimental library integrating LLM capabilities to support causal analyses☆224Updated 2 weeks ago
- TabDPT: Scaling Tabular Foundation Models on Real Data☆33Updated this week
- Unofficial implementation of Conformal Language Modeling by Quach et al☆29Updated 2 years ago
- Conformal Language Modeling☆31Updated last year
- This is the repo for constructing a comprehensive and rigorous evaluation framework for LLM calibration.☆13Updated last year
- A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.☆246Updated last month
- ☆14Updated 3 years ago
- Context is Key: A Benchmark for Forecasting with Essential Textual Information☆66Updated this week
- Code for multistep feedback covariate shift conformal prediction experiments in "Conformal Validity Guarantees Exist for Any Data Distrib…☆27Updated last year
- Code for the paper "Local Causal Discovery for Estimating Causal Effects".☆10Updated last year
- Testing Language Models for Memorization of Tabular Datasets.☆34Updated 5 months ago
- Notebooks for Applied Causal Inference Powered by ML and AI☆127Updated 3 months ago
- A Python toolbox for conformal prediction research on deep learning models, using PyTorch.☆402Updated last week
- CSuite: A Suite of Benchmark Datasets for Causality☆68Updated 2 years ago
- ☆14Updated 2 years ago