implementation of Wasserstein Natural Policy Gradients and Wasserstein Natural Evolution Strategies
☆13Mar 9, 2021Updated 4 years ago
Alternatives and similar repositories for WNPG
Users that are interested in WNPG are comparing it to the libraries listed below
Sorting:
- Code for the paper "Learning Step-Size Adaptation in CMA-ES"☆12Mar 24, 2023Updated 2 years ago
- ☆23Updated this week
- A Pytorch implementation of the KWNG estimator☆14Jul 25, 2024Updated last year
- ☆17Dec 12, 2020Updated 5 years ago
- ☆21Dec 8, 2022Updated 3 years ago
- Bayesian Optimization with Density-Ratio Estimation☆24Dec 26, 2022Updated 3 years ago
- Open source demo for the paper Learning to Score Behaviors for Guided Policy Optimization☆24Jun 24, 2020Updated 5 years ago
- A Julia package for consensus-based optimisation☆16Nov 28, 2025Updated 3 months ago
- (GECCO 2022) CMA-ES with Margin: Lower-Bounding Marginal Probability for Mixed-Integer Black-Box Optimization☆33Mar 20, 2024Updated last year
- Paper: Challenges in High-dimensional Reinforcement Learning with Evolution Strategies☆29May 30, 2022Updated 3 years ago
- Implementation and evaluation of Almanac (Automaton/Logic Multi-Agent Natural Actor-Critic), an algorithm for multi-agent reinforcement l…☆10May 5, 2022Updated 3 years ago
- Introduction to Machine Learning using scikit-learn and PyTorch☆10Sep 26, 2019Updated 6 years ago
- Automated Quantitative Trait Locus Analysis (AutoQTL)☆10Mar 5, 2024Updated last year
- Code for the paper "Semi-Conditional Normalizing Flows for Semi-Supervised Learning"☆11Mar 30, 2020Updated 5 years ago
- ☆11Jun 18, 2023Updated 2 years ago
- Scala発火村の資料ですお☆30Oct 18, 2010Updated 15 years ago
- The SOLAR blackbox optimization problem☆16Sep 24, 2025Updated 5 months ago
- ☆10Jul 5, 2019Updated 6 years ago
- MO-LightGBM is a gradient boosting framework based on decision tree algorithms, used for Multi-objective learning to rank tasks.☆18Apr 23, 2025Updated 10 months ago
- Parallelised Thompson Sampling in GPs for Bayesian Optimisation☆36Sep 23, 2017Updated 8 years ago
- on-policy optimization baselines for deep reinforcement learning☆32Apr 3, 2020Updated 5 years ago
- UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs☆11Apr 13, 2023Updated 2 years ago
- ☆11Dec 19, 2023Updated 2 years ago
- A list of all papers related to anomaly detection in NeurIPS 2020.☆10Jan 13, 2021Updated 5 years ago
- NOMU: Neural Optimization-based Model Uncertainty☆10Feb 17, 2023Updated 3 years ago
- Prompt-Guided Retrieval For Non-Knowledge-Intensive Tasks☆12Sep 1, 2023Updated 2 years ago
- The High-dimensional BayesOpt algorithms from "A Framework for Bayesian Optimization in Embedded Subspaces☆43Jun 8, 2019Updated 6 years ago
- Active Learning Helps Pretrained Models Learn the Intended Task (https://arxiv.org/abs/2204.08491) by Alex Tamkin, Dat Nguyen, Salil Desh…☆11Nov 22, 2022Updated 3 years ago
- ☆10Mar 6, 2022Updated 3 years ago
- LIDA: Lightweight Interactive Dialogue Annotator (in EMNLP 2019)☆10Oct 18, 2021Updated 4 years ago
- Source code and data for More food, more water, less carbon? Costs and benefits of global land-use optimality☆11Sep 21, 2023Updated 2 years ago
- The companion code to the paper "Model-based Causal Bayesian Optimization"☆11Nov 16, 2022Updated 3 years ago
- Bayesian Optimization for Anything: A high-level Bayesian optimization framework and model wrapping toolkit. It provides an easy-to-use i…☆12Dec 18, 2024Updated last year
- ☆10Jan 28, 2024Updated 2 years ago
- Implementation of Stochastic Gradient Descent algorithms in Python (cite https://doi.org/10.1007/s00158-020-02599-z)☆11May 19, 2021Updated 4 years ago
- Bayesian scaling laws for in-context learning.☆15Mar 12, 2025Updated 11 months ago
- Code for EMNLP'24 paper - On Diversified Preferences of Large Language Model Alignment☆16Aug 6, 2024Updated last year
- ☆12Jan 25, 2026Updated last month
- ☆13Oct 16, 2024Updated last year