research
∙
02/07/2023
Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations
In this paper, we present a machine learning method for the discovery of...
share
research
∙
05/14/2022
PrefixRL: Optimization of Parallel Prefix Circuits using Deep Reinforcement Learning
In this work, we present a reinforcement learning (RL) based approach to...
research
∙
02/24/2022
AutoIP: A United Framework to Integrate Physics into Gaussian Processes
Physics modeling is critical for modern science and engineering applicat...
research
∙
10/25/2021
Transformations for Piola-mapped elements
The Arnold-Winther element successfully discretizes the Hellinger-Reissn...
research
∙
10/16/2021
Meta-Learning with Adjoint Methods
Model Agnostic Meta-Learning (MAML) is widely used to find a good initia...
research
∙
09/06/2021
Guiding Global Placement With Reinforcement Learning
Recent advances in GPU accelerated global and detail placement have redu...
research
∙
06/08/2020
Physics Regularized Gaussian Processes
We consider incorporating incomplete physics knowledge, expressed as dif...
research
∙
06/08/2020
Multi-Fidelity High-Order Gaussian Processes for Physical Simulation
The key task of physical simulation is to solve partial differential equ...
research
∙
11/02/2018
SDCNet: Video Prediction Using Spatially-Displaced Convolution
We present an approach for high-resolution video frame prediction by con...
research
∙
08/03/2018