mlsanityData to 7 Oct 2026

EvoTorch: Scalable Evolutionary Computation in Python

arXiv 2302.12600 ↗First posted 24 Feb 2023cs.NE cs.AIcited by 8

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Abstract (arXiv)

Evolutionary computation is an important component within various fields such as artificial intelligence research, reinforcement learning, robotics, industrial automation and/or optimization, engineering design, etc. Considering the increasing computational demands and the dimensionalities of modern optimization problems, the requirement for scalable, re-usable, and practical evolutionary algorithm implementations has been growing. To address this requirement, we present EvoTorch: an evolutionary computation library designed to work with high-dimensional optimization problems, with GPU support and with high parallelization capabilities. EvoTorch is based on and seamlessly works with the PyTorch library, and therefore, allows the users to define their optimization problems using a well-known API.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 20 of its 65 references that are in the map. First posted on arXiv 24 Feb 2023.

Builds on

20 of 65 references.

References · 20

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2019Fast Graph Representation Learning with PyTorch Geometriccited by 2,414
  4. 2016OpenAI Gymcited by 1,684
  5. 2014Deep Learning in Neural Networks: An Overviewcited by 765
  6. 2017Evolution Strategies as a Scalable Alternative to Reinforcement Learningcited by 555
  7. 2017Ray: A Distributed Framework for Emerging AI Applicationscited by 516
  8. 2015Illuminating search spaces by mapping elitescited by 406
  9. 2021Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulationcited by 375
  10. 2018AllenNLP: A Deep Semantic Natural Language Processing Platformcited by 347
  11. 2020pymoo: Multi-objective Optimization in Pythoncited by 196
  12. 2018Reinforcement Learning for Improving Agent Designcited by 55
8 more
  1. 2022TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discoverycited by 45
  2. 2022evosax: JAX-based Evolution Strategiescited by 39
  3. 2022EvoJAX: Hardware-Accelerated Neuroevolutioncited by 29
  4. 2018EA-LSTM: Evolutionary Attention-based LSTM for Time Series Predictioncited by 26
  5. 2017ES Is More Than Just a Traditional Finite-Difference Approximatorcited by 24
  6. 2017On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descentcited by 16
  7. 2019Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methodscited by 8
  8. 2020ClipUp: A Simple and Powerful Optimizer for Distribution-based Policy Evolutioncited by 7

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 4; 2026: 3.

8 papers.

  1. 2024LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorchcited by 10
  2. 2025G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibrationcited by 8
  3. 2025Enabling Population-Level Parallelism in Tree-Based Genetic Programming for GPU Accelerationcited by 3
  4. 2025A Design Co-Pilot for Task-Tailored Manipulatorscited by 2
  5. 2025Inference-Time Alignment of Diffusion Models via Evolutionary Algorithmscited by 1
  6. 2026Agentic Architect: An Agentic AI Framework for Architecture Design Exploration and Optimizationcited by 1
  7. 2026GIF: Agentic Generation of Interactive and Functional Object Compositions for Robot Learningcited by 1
  8. 2026Real-time Rendering-based Surgical Instrument Tracking via Evolutionary Optimizationcited by 0