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.
☆43Updated 6 months ago
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:
- A package for conformal prediction with conditional guarantees.☆67Updated 2 months ago
- Resources for education in statistics and machine learning: from advanced undergraduate to research level☆103Updated last year
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆177Updated last year
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆45Updated 2 years ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆73Updated 2 years ago
- ☆68Updated 9 months ago
- Conformal Language Modeling☆32Updated 2 years ago
- Unofficial implementation of Conformal Language Modeling by Quach et al☆29Updated 2 years ago
- Extending Conformal Prediction to LLMs☆68Updated last year
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆99Updated 10 months ago
- ☆14Updated 3 years ago
- Public dataset repository for the Causal Chamber Project☆54Updated last month
- ☆194Updated 2 years ago
- ☆15Updated 3 years ago
- This is the repo for constructing a comprehensive and rigorous evaluation framework for LLM calibration.☆13Updated last year
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆73Updated last year
- Course materials for Advanced Topics in Statistical Learning, Spring 2024☆26Updated 5 months ago
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆33Updated 2 years ago
- Context is Key: A Benchmark for Forecasting with Essential Textual Information☆84Updated 4 months ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆69Updated 10 months ago
- ☆241Updated last year
- ☆33Updated last year
- Conditional calibration of conformal p-values for outlier detection.☆37Updated 3 years ago
- A curated list of Robust Machine Learning papers/articles and recent advancements.☆33Updated 3 years ago
- pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation☆141Updated 3 months ago
- Inference code for "TabDPT: Scaling Tabular Foundation Models on Real Data"☆66Updated last week
- Tabular In-Context Learning☆101Updated 9 months ago
- CausalPFN: Amortized Causal Effect Estimation via In-Context Learning☆84Updated 3 weeks ago
- Testing Language Models for Memorization of Tabular Datasets.☆36Updated 10 months ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆88Updated last year