Jay Pathak

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 23

Top Topics

Unsupervised Learning

Explicit Expressions

Top Venues

Eng. Appl. Artif. Intell.

Publications

Zongren Zou, Adar Kahana, Enrui Zhang, Eli Turkel, Rishikesh Ranade, Jay Pathak, George Em Karniadakis
Large scale scattering using fast solvers based on neural operators. CoRR (2024)
Rucha Apte, Sheel Nidhan, Rishikesh Ranade, Jay Pathak
Diffusion model based data generation for partial differential equations. CoRR (2023)
Enrui Zhang, Adar Kahana, Eli Turkel, Rishikesh Ranade, Jay Pathak, George Em Karniadakis
A Hybrid Iterative Numerical Transferable Solver (HINTS) for PDEs Based on Deep Operator Network and Relaxation Methods. CoRR (2022)
Rishikesh Ranade, Chris Hill, Lalit Ghule, Jay Pathak
A composable machine-learning approach for steady-state simulations on high-resolution grids. CoRR (2022)
Adar Kahana, Enrui Zhang, Somdatta Goswami, George Em Karniadakis, Rishikesh Ranade, Jay Pathak
On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations. CoRR (2022)
Rishikesh Ranade, Chris Hill, Lalit Ghule, Jay Pathak
A composable machine-learning approach for steady-state simulations on high-resolution grids. NeurIPS (2022)
Lalit Ghule, Rishikesh Ranade, Jay Pathak
NLP Inspired Training Mechanics For Modeling Transient Dynamics. CoRR (2022)
Rishikesh Ranade, Haiyang He, Jay Pathak, Norman Chang, Akhilesh Kumar, Jimin Wen
A Thermal Machine Learning Solver For Chip Simulation. MLCAD (2022)
Rishikesh Ranade, Haiyang He, Jay Pathak, Norman Chang, Akhilesh Kumar, Jimin Wen
A Thermal Machine Learning Solver For Chip Simulation. CoRR (2022)
Lu Lu, Haiyang He, Priya Kasimbeg, Rishikesh Ranade, Jay Pathak
One-shot learning for solution operators of partial differential equations. CoRR (2021)
Rishikesh Ranade, Jay Pathak
ActivationNet: Representation learning to predict contact quality of interacting 3-D surfaces in engineering designs. CoRR (2021)
Rishikesh Ranade, Chris Hill, Haiyang He, Amir Maleki, Jay Pathak
A Latent space solver for PDE generalization. CoRR (2021)
Jaydeep Rade, Aditya Balu, Ethan Herron, Jay Pathak, Rishikesh Ranade, Soumik Sarkar, Adarsh Krishnamurthy
Algorithmically-consistent deep learning frameworks for structural topology optimization. Eng. Appl. Artif. Intell. 106 (2021)
Amir Maleki, Jan Heyse, Rishikesh Ranade, Haiyang He, Priya Kasimbeg, Jay Pathak
Geometry encoding for numerical simulations. CoRR (2021)
Rishikesh Ranade, Chris Hill, Haiyang He, Amir Maleki, Norman Chang, Jay Pathak
A composable autoencoder-based iterative algorithm for accelerating numerical simulations. CoRR (2021)
Jay Pathak, Anand D. Darji
Analysis of Standard Cells performance for In0.53Ga0.47As FinFET with underlap fin length for High Speed Applications. VDAT (2021)
Haiyang He, Jay Pathak
An unsupervised learning approach to solving heat equations on chip based on Auto Encoder and Image Gradient. CoRR (2020)
Jaydeep Rade, Aditya Balu, Ethan Herron, Jay Pathak, Rishikesh Ranade, Soumik Sarkar, Adarsh Krishnamurthy
Physics-consistent deep learning for structural topology optimization. CoRR (2020)
Rishikesh Ranade, Chris Hill, Jay Pathak
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization. CoRR (2020)
Tiffany Fan, Kailai Xu, Jay Pathak, Eric Darve
Solving Inverse Problems in Steady State Navier-Stokes Equations using Deep Neural Networks. CoRR (2020)
Jay Pathak, Anand D. Darji
As FinFET with gate-to-source/drain underlap for sub-14 nm technology node to impede short channel effect. IET Circuits Devices Syst. 13 (4) (2019)
Jay Pathak, Anand D. Darji
Stability Analysis of SRAM Designed Using In0.53Ga0.47As nFinFET with Underlap Region. VLSI Design (2019)
Jay Pathak, Anand D. Darji
Investigation of TCADs Models for Characterization of Sub 16 nm In _0.53 Ga _0.47 As FinFET. VDAT (2017)