mlsanityData to 14 Oct 2026

TherML: Thermodynamics of Machine Learning

arXiv 1807.04162 ↗First posted 11 Jul 2018cs.LG cond-mat.stat-mech stat.MLcited by 9

Not on the map. Why?

Abstract (arXiv)

In this work we offer a framework for reasoning about a wide class of existing objectives in machine learning. We develop a formal correspondence between this work and thermodynamics and discuss its implications.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Jul 2018.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 3; 2022: 2; 2023: 1; 2024: 1; 2025: 2.

9 papers.

  1. 2023Thermodynamic AI and the fluctuation frontiercited by 15
  2. 2021Differentiable Physics: A Position Piececited by 12
  3. 2021An Exploration of Learnt Representations of W Jetscited by 8
  4. 2025SGD as Free Energy Minimization: A Thermodynamic View on Neural Network Trainingcited by 4
  5. 2022Machine-Learning Compression for Particle Physics Discoveriescited by 3
  6. 2025First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Modelscited by 3
  7. 2021Rethinking Neural Networks With Benford's Lawcited by 2
  8. 2024The Phenomenology of Machine: A Comprehensive Analysis of the Sentience of the OpenAI-o1 Model Integrating Functionalism, Consciousness Theories, Active Inference, and AI Architecturescited by 1
  9. 2022Pareto-optimal clustering with the primal deterministic information bottleneckcited by 0