Rishikesh Ranade

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 21

Top Topics

Density Function

Partial Differential Equations

Top Venues

Eng. Appl. Artif. Intell.

Publications

Priyesh Kakka, Sheel Nidhan, Rishikesh Ranade, Jonathan F. MacArt
Sampling-based Distributed Training with Message Passing Neural Network. CoRR (2024)
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)
Haiyang He, Norman Chang, Jie Yang, Akhilesh Kumar, Wenbo Xia, Lang Lin, Rishikesh Ranade
Invited Paper: Solving Fine-Grained Static 3DIC Thermal with ML Thermal Solver Enhanced with Decay Curve Characterization. ICCAD (2023)
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)
Rishikesh Ranade, Kevin Gitushi, Tarek Echekki
Generalized Joint Probability Density Function Formulation inTurbulent Combustion using DeepONet. CoRR (2021)
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)
Rishikesh Ranade, Genong Li, Shaoping Li, Tarek Echekki
An Efficient Machine-Learning Approach for PDF Tabulation in Turbulent Combustion Closure. 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)