Useful Starting Point: 2022 LLVM Developers' Meeting ------ LAGrad: Leveraging the MLIR Ecosystem for Efficient ... Jan Drgona, Pacific Northwest National Laboratory July 10, 2024 Fourth Symposium on Machine Learning and Dynamical ...

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2022 LLVM Developers' Meeting ------ LAGrad: Leveraging the MLIR Ecosystem for Efficient ... In the ideal world, we describe our models with recognizable mathematical expressions and directly fit those models to large data ... Jan Drgona, Pacific Northwest National Laboratory July 10, 2024 Fourth Symposium on Machine Learning and Dynamical ...

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Jan Drgona, Pacific Northwest National Laboratory July 10, 2024 Fourth Symposium on Machine Learning and Dynamical ... Ján Drgoňa, PNNL, Johns Hopkins University (JHU) Abstract: This talk will present a different ...

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  • 2022 LLVM Developers' Meeting ------ LAGrad: Leveraging the MLIR Ecosystem for Efficient ...
  • In the ideal world, we describe our models with recognizable mathematical expressions and directly fit those models to large data ...
  • Jan Drgona, Pacific Northwest National Laboratory July 10, 2024 Fourth Symposium on Machine Learning and Dynamical ...
  • Ján Drgoňa, PNNL, Johns Hopkins University (JHU) Abstract: This talk will present a different ...

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Media Gallery

PyHEP2022 Analysis Optimisation with Differentiable Programming
PyHEP2022 Speeding up differentiable programming with a Computer Algebra System
Differentiable Programming for Data-driven Modeling, Optimization, and Control
Differentiable Programming in HEP
Differentiable Programming (Part 1)
2022 LLVM Dev Mtg: LAGrad: Leveraging the MLIR Ecosystem for Efficient Differentiable Programming
Differentiable Programming for Data-driven Modeling, Optimization, and Control
Coarsening Optimization for Differentiable Programming
Differentiable Programming with Julia by Mike Innes
OOPSLA21 teaser: How to Speed Up Differentiable Programming by 300X
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PyHEP2022 Analysis Optimisation with Differentiable Programming

PyHEP2022 Analysis Optimisation with Differentiable Programming

Read more details and related context about PyHEP2022 Analysis Optimisation with Differentiable Programming.

PyHEP2022 Speeding up differentiable programming with a Computer Algebra System

PyHEP2022 Speeding up differentiable programming with a Computer Algebra System

In the ideal world, we describe our models with recognizable mathematical expressions and directly fit those models to large data ...

Differentiable Programming for Data-driven Modeling, Optimization, and Control

Differentiable Programming for Data-driven Modeling, Optimization, and Control

Jan Drgona, Pacific Northwest National Laboratory July 10, 2024 Fourth Symposium on Machine Learning and Dynamical ...

Differentiable Programming in HEP

Differentiable Programming in HEP

Read more details and related context about Differentiable Programming in HEP.

Differentiable Programming (Part 1)

Differentiable Programming (Part 1)

Read more details and related context about Differentiable Programming (Part 1).

2022 LLVM Dev Mtg: LAGrad: Leveraging the MLIR Ecosystem for Efficient Differentiable Programming

2022 LLVM Dev Mtg: LAGrad: Leveraging the MLIR Ecosystem for Efficient Differentiable Programming

2022 LLVM Developers' Meeting ------ LAGrad: Leveraging the MLIR Ecosystem for Efficient ...

Differentiable Programming for Data-driven Modeling, Optimization, and Control

Differentiable Programming for Data-driven Modeling, Optimization, and Control

Ján Drgoňa, PNNL, Johns Hopkins University (JHU) Abstract: This talk will present a different ...

Coarsening Optimization for Differentiable Programming

Coarsening Optimization for Differentiable Programming

Read more details and related context about Coarsening Optimization for Differentiable Programming.

Differentiable Programming with Julia by Mike Innes

Differentiable Programming with Julia by Mike Innes

Read more details and related context about Differentiable Programming with Julia by Mike Innes.

OOPSLA21 teaser: How to Speed Up Differentiable Programming by 300X

OOPSLA21 teaser: How to Speed Up Differentiable Programming by 300X

Read more details and related context about OOPSLA21 teaser: How to Speed Up Differentiable Programming by 300X.