Search Results for author: Stefano Martiniani

Found 7 papers, 3 papers with code

Open Materials Generation with Stochastic Interpolants

no code implementations4 Feb 2025 Philipp Hoellmer, Thomas Egg, Maya M. Martirossyan, Eric Fuemmeler, Amit Gupta, Zeren Shui, Pawan Prakash, Adrian Roitberg, Mingjie Liu, George Karypis, Mark Transtrum, Richard G. Hennig, Ellad B. Tadmor, Stefano Martiniani

We benchmark OMG's performance on two tasks: Crystal Structure Prediction (CSP) for specified compositions, and 'de novo' generation (DNG) aimed at discovering stable, novel, and unique structures.

Unconditional stability of a recurrent neural circuit implementing divisive normalization

1 code implementation27 Sep 2024 Shivang Rawat, David J. Heeger, Stefano Martiniani

Stability in recurrent neural models poses a significant challenge, particularly in developing biologically plausible neurodynamical models that can be seamlessly trained.

Image Classification

On the design space between molecular mechanics and machine learning force fields

no code implementations3 Sep 2024 Yuanqing Wang, Kenichiro Takaba, Michael S. Chen, Marcus Wieder, Yuzhi Xu, Tong Zhu, John Z. H. Zhang, Arnav Nagle, Kuang Yu, Xinyan Wang, Daniel J. Cole, Joshua A. Rackers, Kyunghyun Cho, Joe G. Greener, Peter Eastman, Stefano Martiniani, Mark E. Tuckerman

A force field as accurate as quantum mechanics (QM) and as fast as molecular mechanics (MM), with which one can simulate a biomolecular system efficiently enough and meaningfully enough to get quantitative insights, is among the most ardent dreams of biophysicists -- a dream, nevertheless, not to be fulfilled any time soon.

Correlation lengths in the language of computable information

2 code implementations7 Apr 2020 Stefano Martiniani, Yuval Lemberg, Paul M. Chaikin, Dov Levine

The correlation length and its critical exponents are thus accessible with no a-priori knowledge of an order parameter or even the nature of the ordering.

Statistical Mechanics Disordered Systems and Neural Networks Soft Condensed Matter Cellular Automata and Lattice Gases Computational Physics

Quantifying hidden order out of equilibrium

1 code implementation16 Aug 2017 Stefano Martiniani, Paul M. Chaikin, Dov Levine

While the equilibrium properties, states, and phase transitions of interacting systems are well described by statistical mechanics, the lack of suitable state parameters has hindered the understanding of non-equilibrium phenomena in diverse settings, from glasses to driven systems to biology.

Soft Condensed Matter Disordered Systems and Neural Networks Statistical Mechanics Computational Physics

Perspective: Energy Landscapes for Machine Learning

no code implementations23 Mar 2017 Andrew J. Ballard, Ritankar Das, Stefano Martiniani, Dhagash Mehta, Levent Sagun, Jacob D. Stevenson, David J. Wales

Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences.

BIG-bench Machine Learning

Monte Carlo sampling for stochastic weight functions

no code implementations19 Dec 2016 Daan Frenkel, K. Julian Schrenk, Stefano Martiniani

Conventional Monte Carlo simulations are stochastic in the sense that the acceptance of a trial move is decided by comparing a computed acceptance probability with a random number, uniformly distributed between 0 and 1.

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