Maziar Raissi - RankMe

57 papers A 1Journal 53Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Data-Efficient Physics-Informed Learning to Model Synchro-Waveform Dynamics of Grid-Integrated Inverter-Based Resources. CoRR Shivanshu Tripathi, Hossein Mohsenzadeh-Yazdi, Maziar Raissi, Hamed Mohsenian Rad
2026	J	`jnl`	Deep Neural Network Parameter Selection via Dataset Similarity Under Meta-Learning Framework. IEEE Trans. Pattern Anal. Mach. Intell. Liping Deng, Maziar Raissi, Mingqing Xiao
2026	J	`jnl`	Meta-Learning-Based Surrogate Models for Efficient Hyperparameter Optimization. IEEE Trans. Pattern Anal. Mach. Intell. Liping Deng, Maziar Raissi, Mingqing Xiao
2026	J	`jnl`	NewPINNs: Physics-Informing Neural Networks Using Conventional Solvers for Partial Differential Equations. CoRR Maedeh Makki, Satish Chandran, Maziar Raissi, Adrien Grenier, Behzad Mohebbi
2026	J	`jnl`	PUNCH: Physics-informed Uncertainty-aware Network for Coronary Hemodynamics. CoRR Sukirt Thakur, Marcus Roper, Yang Zhou, Reza Akbarian Bafghi, Brahmajee K. Nallamothu, C. Alberto Figueroa, Srinivas Paruchuri, Scott Burger, Maziar Raissi
2026	J	`jnl`	Test-Driven Agentic Framework for Reliable Robot Controller. CoRR Shivanshu Tripathi, Reza Akbarian Bafghi, Maziar Raissi
2025	J	`jnl`	A survey on physics informed reinforcement learning: Review and open problems. Expert Syst. Appl. Chayan Banerjee, Kien Nguyen Thanh, Clinton Fookes, Maziar Raissi
2025	—	`conf`	Aligning to What? Limits to RLHF Based Alignment. NAACL (Findings) Logan Barnhart, Reza Akbarian Bafghi, Stephen Becker, Maziar Raissi
2025	J	`jnl`	Aligning to What? Limits to RLHF Based Alignment. CoRR Logan Barnhart, Reza Akbarian Bafghi, Stephen Becker, Maziar Raissi
2025	J	`jnl`	Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation. CoRR Reza Akbarian Bafghi, Carden Bagwell, Avinash Ravichandran, Ashish Shrivastava, Maziar Raissi
2025	A	`conf`	MixDiff: Mixing Natural and Synthetic Images for Robust Self-Supervised Representations. WACV Reza Akbarian Bafghi, Nidhin Harilal, Claire Monteleoni, Maziar Raissi
2024	J	`jnl`	Deep LPPLS: Forecasting of temporal critical points in natural, engineering and financial systems. CoRR Joshua Nielsen, Didier Sornette, Maziar Raissi
2024	J	`jnl`	Guest Editorial: Special Issue on Physics-Informed Machine Learning. IEEE Trans. Artif. Intell. Francesco Piccialli, Maziar Raissi, Felipe A. C. Viana, Giancarlo Fortino, Huimin Lu, Amir Hussain
2024	J	`jnl`	Mixing Natural and Synthetic Images for Robust Self-Supervised Representations. CoRR Reza Akbarian Bafghi, Nidhin Harilal, Claire Monteleoni, Maziar Raissi
2024	—	`conf`	Parameter Efficient Fine-tuning of Self-supervised ViTs without Catastrophic Forgetting. CVPR Workshops Reza Akbarian Bafghi, Nidhin Harilal, Claire Monteleoni, Maziar Raissi
2024	—	`conf`	Parameter Efficient Fine-tuning of Self-supervised ViTs without Catastrophic Forgetting. CVPR Workshops Reza Akbarian Bafghi, Nidhin Harilal, Claire Monteleoni, Maziar Raissi
2024	J	`jnl`	Parameter Efficient Fine-tuning of Self-supervised ViTs without Catastrophic Forgetting. CoRR Reza Akbarian Bafghi, Nidhin Harilal, Claire Monteleoni, Maziar Raissi
2024	J	`jnl`	Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing: Fluid and Solid Mechanics. J. Comput. Inf. Sci. Eng. Salah A. Faroughi, Nikhil M. Pawar, Célio Fernandes, Maziar Raissi, Subasish Das, Nima K. Kalantari, Seyed Kourosh Mahjour
2024	J	`jnl`	Physics-Informed Machine Learning for Smart Additive Manufacturing. CoRR Rahul Sharma, Maziar Raissi, Y. B. Guo
2024	J	`jnl`	Physics-Informed Neural Networks and Extensions. CoRR Maziar Raissi, Paris Perdikaris, Nazanin Ahmadi Daryakenari, George Em Karniadakis
2024	J	`jnl`	Where Did Your Model Learn That? Label-free Influence for Self-supervised Learning. CoRR Nidhin Harilal, Amit Kiran Rege, Reza Akbarian Bafghi, Maziar Raissi, Claire Monteleoni
2023	J	`jnl`	A Survey on Physics Informed Reinforcement Learning: Review and Open Problems. CoRR Chayan Banerjee, Kien Nguyen, Clinton Fookes, Maziar Raissi
2023	J	`jnl`	Open Problems in Applied Deep Learning. CoRR Maziar Raissi
2023	J	`jnl`	PINNs-TF2: Fast and User-Friendly Physics-Informed Neural Networks in TensorFlow V2. CoRR Reza Akbarian Bafghi, Maziar Raissi
2023	J	`jnl`	Physics-Informed Machine Learning of Argon Gas-Driven Melt Pool Dynamics. CoRR Rahul Sharma, W. Grace Guo, Maziar Raissi, Yuebin Guo
2023	J	`jnl`	Real Estate Property Valuation using Self-Supervised Vision Transformers. CoRR Mahdieh Yazdani, Maziar Raissi
2023	J	`jnl`	Temporal Consistency Loss for Physics-Informed Neural Networks. CoRR Sukirt Thakur, Maziar Raissi, Harsa Mitra, Arezoo M. Ardekani
2022	J	`jnl`	Scientific Machine Learning Through Physics-Informed Neural Networks: Where we are and What's Next. J. Sci. Comput. Salvatore Cuomo, Vincenzo Schiano Di Cola, Fabio Giampaolo, Gianluigi Rozza, Maziar Raissi, Francesco Piccialli
2022	J	`jnl`	Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next. CoRR Salvatore Cuomo, Vincenzo Schiano Di Cola, Fabio Giampaolo, Gianluigi Rozza, Maziar Raissi, Francesco Piccialli
2021	J	`jnl`	Call for Special Issue Papers: Big Scientific Data and Machine Learning in Science and Engineering: Deadline for Manuscript Submission: February 1, 2022. Big Data Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Stephen Becker, Maziar Raissi
2021	J	`jnl`	Call for Special Issue Papers: Big Scientific Data and Machine Learning in Science and Engineering: Deadline for Manuscript Submission: February 1, 2022. Big Data Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Stephen Becker, Maziar Raissi
2021	J	`jnl`	Call for Special Issue Papers: Big Scientific Data and Machine Learning in Science and Engineering: Deadline for Manuscript Submission: February 1, 2022. Big Data Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Stephen Becker, Maziar Raissi
2021	J	`jnl`	Disease Informed Neural Networks. CoRR Sagi Shaier, Maziar Raissi
2020	J	`jnl`	A deep learning framework for solution and discovery in solid mechanics: linear elasticity. CoRR Ehsan Haghighat, Maziar Raissi, Adrian Moure, Héctor Gómez, Ruben Juanes
2020	J	`jnl`	Systems biology informed deep learning for inferring parameters and hidden dynamics. PLoS Comput. Biol. Alireza Yazdani, Lu Lu, Maziar Raissi, George Em Karniadakis
2019	J	`jnl`	Machine Learning of Space-Fractional Differential Equations. SIAM J. Sci. Comput. Mamikon A. Gulian, Maziar Raissi, Paris Perdikaris, George E. Karniadakis
2019	J	`jnl`	Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. J. Comput. Phys. Maziar Raissi, Paris Perdikaris, George E. Karniadakis
2018	J	`jnl`	Application of local improvements to reduced-order models to sampling methods for nonlinear PDEs with noise. Int. J. Comput. Math. Maziar Raissi, Padmanabhan Seshaiyer
2018	J	`jnl`	Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations. CoRR Maziar Raissi
2018	J	`jnl`	Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations. J. Mach. Learn. Res. Maziar Raissi
2018	J	`jnl`	Deep Learning of Turbulent Scalar Mixing. CoRR Maziar Raissi, Hessam Babaee, Peyman Givi
2018	J	`jnl`	Deep Learning of Vortex Induced Vibrations. CoRR Maziar Raissi, Zhicheng Wang, Michael S. Triantafyllou, George E. Karniadakis
2018	J	`jnl`	Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations. CoRR Maziar Raissi
2018	J	`jnl`	Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data. CoRR Maziar Raissi, Alireza Yazdani, George E. Karniadakis
2018	J	`jnl`	Hidden physics models: Machine learning of nonlinear partial differential equations. J. Comput. Phys. Maziar Raissi, George E. Karniadakis
2018	J	`jnl`	Machine Learning of Space-Fractional Differential Equations. CoRR Mamikon A. Gulian, Maziar Raissi, Paris Perdikaris, George E. Karniadakis
2018	J	`jnl`	Numerical Gaussian Processes for Time-Dependent and Nonlinear Partial Differential Equations. SIAM J. Sci. Comput. Maziar Raissi, Paris Perdikaris, George E. Karniadakis
2017	J	`jnl`	Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations. CoRR Maziar Raissi, George E. Karniadakis
2017	J	`jnl`	Inferring solutions of differential equations using noisy multi-fidelity data. J. Comput. Phys. Maziar Raissi, Paris Perdikaris, George E. Karniadakis
2017	J	`jnl`	Machine Learning of Linear Differential Equations using Gaussian Processes. CoRR Maziar Raissi, George E. Karniadakis
2017	J	`jnl`	Machine learning of linear differential equations using Gaussian processes. J. Comput. Phys. Maziar Raissi, Paris Perdikaris, George E. Karniadakis
2017	J	`jnl`	Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations. CoRR Maziar Raissi, Paris Perdikaris, George E. Karniadakis
2017	J	`jnl`	Parametric Gaussian Process Regression for Big Data. CoRR Maziar Raissi
2017	J	`jnl`	Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations. CoRR Maziar Raissi, Paris Perdikaris, George E. Karniadakis
2017	J	`jnl`	Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations. CoRR Maziar Raissi, Paris Perdikaris, George E. Karniadakis
2016	J	`jnl`	Deep Multi-fidelity Gaussian Processes. CoRR Maziar Raissi, George E. Karniadakis
2016	J	`jnl`	Inferring solutions of differential equations using noisy multi-fidelity data. CoRR Maziar Raissi, Paris Perdikaris, George E. Karniadakis