Anima Anandkumar on Muck Rack

Anima Anandkumar

Ithaca
As seen in: Medium, Nature, IEEE Spectrum, Caltech, Science Magazine, Physical Review B, Quanta Magazine, Pasadena Now, SIAM News, News India Times and
AI+Science, Bren Professor @caltech, Time100, Fmr Sr Director of #AI research @nvidia Fmr Principal Scientist @awscloud
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Articles

Fourier neural operators for learning dynamics in quantum spin systems

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By Freya Shah, Taylor L. Patti, Julius Berner, Bahareh Tolooshams, Jean Kossaifi, Anima Anandkumar
| Nature
Abstract Fourier Neural Operators (FNOs) excel on functional data tasks, such as those originating from partial differential equations. This renders them effective at simulating the time evolution of quantum wavefunctions, a computationally challenging, yet coveted task. In this manuscript, we use FNOs to model the evolution of random quantum spin systems, chosen due to their representative dynamics.
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Formalizing Neural Networks in Lean

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By Anima Anandkumar
| leandojo.org
Abstract Neural networks are increasingly deployed in safety- and mission-critical pipelines, yet many verification and analysis results are produced outside the programming environment that defines and runs the model. This separation creates a semantic gap between the executed network and the analyzed artifact, so guarantees can hinge on implicit conventions such as operator semantics, tensor layouts, preprocessing, and floating-point corner cases.
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Sequence-based generative AI design of versatile tryptophan synthases - Nature Communications

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By Jason Yang, Vignesh C. Bhethanabotla, Arvind Ramanathan, Anima Anandkumar, Théophile Lambert
| Nature
Abstract Enzymes are powerful and sustainable catalysts, but their widespread application is limited by the difficulty of identifying functional starting points for optimization, creating a major bottleneck in early- stage biocatalyst discovery. Designing libraries of such starting enzymes remains particularly challenging.
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