DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization. - Rishikesh Ranade; Chris Hill; Jay Pathak (CoRR, 2020)

An Efficient Machine-Learning Approach for PDF Tabulation in Turbulent Combustion Closure. - Rishikesh Ranade; Genong Li; Shaoping Li; Tarek Echekki (CoRR, 2020)

Physics-consistent deep learning for structural topology optimization. - Jaydeep Rade; Aditya Balu; Ethan Herron; Jay Pathak; Rishikesh Ranade; Soumik Sarkar; Adarsh Krishnamurthy (CoRR, 2020)

ActivationNet: Representation learning to predict contact quality of interacting 3-D surfaces in engineering designs. - Rishikesh Ranade; Jay Pathak (CoRR, 2021)

Generalized Joint Probability Density Function Formulation inTurbulent Combustion using DeepONet. - Rishikesh Ranade; Kevin Gitushi; Tarek Echekki (CoRR, 2021)

A Latent space solver for PDE generalization. - Rishikesh Ranade; Chris Hill; Haiyang He; Amir Maleki; Jay Pathak (CoRR, 2021)

One-shot learning for solution operators of partial differential equations. - Lu Lu; Haiyang He; Priya Kasimbeg; Rishikesh Ranade; Jay Pathak (CoRR, 2021)

Geometry encoding for numerical simulations. - Amir Maleki; Jan Heyse; Rishikesh Ranade; Haiyang He; Priya Kasimbeg; Jay Pathak (CoRR, 2021)

A composable autoencoder-based iterative algorithm for accelerating numerical simulations. - Rishikesh Ranade; Chris Hill; Haiyang He; Amir Maleki; Norman Chang; Jay Pathak (CoRR, 2021)

Algorithmically-consistent deep learning frameworks for structural topology optimization. - Jaydeep Rade; Aditya Balu; Ethan Herron; Jay Pathak; Rishikesh Ranade; Soumik Sarkar; Adarsh Krishnamurthy (Eng. Appl. Artif. Intell., 2021)

A Thermal Machine Learning Solver For Chip Simulation. - Rishikesh Ranade; Haiyang He; Jay Pathak; Norman Chang; Akhilesh Kumar; Jimin Wen (MLCAD, 2022)

A composable machine-learning approach for steady-state simulations on high-resolution grids. - Rishikesh Ranade; Chris Hill; Lalit Ghule; Jay Pathak (NeurIPS, 2022)

A Hybrid Iterative Numerical Transferable Solver (HINTS) for PDEs Based on Deep Operator Network and Relaxation Methods. - Enrui Zhang; Adar Kahana; Eli Turkel; Rishikesh Ranade; Jay Pathak; George Em Karniadakis (CoRR, 2022)

On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations. - Adar Kahana; Enrui Zhang; Somdatta Goswami; George Em Karniadakis; Rishikesh Ranade; Jay Pathak (CoRR, 2022)

NLP Inspired Training Mechanics For Modeling Transient Dynamics. - Lalit Ghule; Rishikesh Ranade; Jay Pathak (CoRR, 2022)

Invited Paper: Solving Fine-Grained Static 3DIC Thermal with ML Thermal Solver Enhanced with Decay Curve Characterization. - Haiyang He; Norman Chang; Jie Yang 023; Akhilesh Kumar; Wenbo Xia; Lang Lin; Rishikesh Ranade (ICCAD, 2023)

Diffusion model based data generation for partial differential equations. - Rucha Apte; Sheel Nidhan; Rishikesh Ranade; Jay Pathak (CoRR, 2023)

Parallel Per-tile Activation with Linear Superposition of Thermal Response for Solving Arbitrary Power Pattern in 3DIC Thermal Simulation. - Haiyang He; Norman Chang; Akhilesh Kumar; Jie Yang 023; Wenbo Xia; Lang Lin; Jessica Yen; Haoliang Jiang; Rishikesh Ranade (MLCAD, 2024)

Sampling-based Distributed Training with Message Passing Neural Network. - Priyesh Kakka; Sheel Nidhan; Rishikesh Ranade; Jonathan F. MacArt (CoRR, 2024)

Large scale scattering using fast solvers based on neural operators. - Zongren Zou; Adar Kahana; Enrui Zhang; Eli Turkel; Rishikesh Ranade; Jay Pathak; George Em Karniadakis (CoRR, 2024)

A domain decomposition-based autoregressive deep learning model for unsteady and nonlinear partial differential equations. - Sheel Nidhan; Haoliang Jiang; Lalit Ghule; Clancy Umphrey; Rishikesh Ranade; Jay Pathak (CoRR, 2024)

Blending neural operators and relaxation methods in PDE numerical solvers. - Enrui Zhang; Adar Kahana; Alena Kopanicáková; Eli Turkel; Rishikesh Ranade; Jay Pathak; George Em Karniadakis (Nat. Mac. Intell., 2024)

DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations. - Rishikesh Ranade; Mohammad Amin Nabian; Kaustubh Tangsali; Alexey Kamenev; Oliver Hennigh; Ram Cherukuri; Sanjay Choudhry (CoRR, 2025)

Accelerating Transient CFD through Machine Learning-Based Flow Initialization. - Peter Sharpe; Rishikesh Ranade; Sanjay Choudhry (CoRR, 2025)

A Benchmarking Framework for AI models in Automotive Aerodynamics. - Kaustubh Tangsali; Rishikesh Ranade; Mohammad Amin Nabian; Alexey Kamenev; Peter Sharpe; Neil Ashton; Ram Cherukuri; Sanjay Choudhry (CoRR, 2025)