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Statistical mechanics meets single-cell biology | Nature Reviews Genetics
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Quantifying Mutational Response to Track the Evolution of SARS-CoV-2 Spike Variants: Introducing a Statistical-Mechanics-Guided Machine Learning Method | The Journal of Physical Chemistry B
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A Tale of Two Probabilities – Alianna J. Maren
The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks: Roberts, Daniel A., Yaida, Sho, Hanin, Boris: 9781316519332: Amazon.com: Books
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Best of arXiv.org for AI, Machine Learning, and Deep Learning – June 2020 - insideBIGDATA
Water | Free Full-Text | Deep Learning Method Based on Physics Informed Neural Network with Resnet Block for Solving Fluid Flow Problems
Frontiers | A Review of the Application of Machine Learning and Data Mining Approaches in Continuum Materials Mechanics
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A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning
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Book – Alianna J. Maren
Recent advances and applications of deep learning methods in materials science | npj Computational Materials
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Informing geometric deep learning with electronic interactions to accelerate quantum chemistry | PNAS
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Boltzmann machine - Wikipedia
CECAM - Machine Learning Meets Statistical Mechanics: Success and Future Challenges in BiosimulationsMachine Learning Meets Statistical Mechanics: Success and Future Challenges in Biosimulations
