default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDAmeya D. Jagtap
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[i14]Ahmad Peyvan, Vivek Oommen, Ameya D. Jagtap, George Em Karniadakis:
RiemannONets: Interpretable Neural Operators for Riemann Problems. CoRR abs/2401.08886 (2024)- [i13]Shuvayan Brahmachary, Subodh M. Joshi, Aniruddha Panda, Kaushik Koneripalli, Arun Kumar Sagotra, Harshil Patel, Ankush Sharma, Ameya D. Jagtap, Kaushic Kalyanaraman:
Large Language Model-Based Evolutionary Optimizer: Reasoning with elitism. CoRR abs/2403.02054 (2024) - 2023
- [j10]Zheyuan Hu
, Ameya D. Jagtap, George Em Karniadakis, Kenji Kawaguchi:
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology. Eng. Appl. Artif. Intell. 126: 107183 (2023) - [j9]Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby:
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions. J. Comput. Phys. 493: 112464 (2023) - [i12]Somdatta Goswami, Ameya D. Jagtap, Hessam Babaee, Bryan T. Susi, George Em Karniadakis:
Learning stiff chemical kinetics using extended deep neural operators. CoRR abs/2302.12645 (2023) - [i11]Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby:
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions. CoRR abs/2302.14227 (2023) - [i10]Tatiana Kossaczká, Ameya D. Jagtap, Matthias Ehrhardt:
Deep smoothness WENO scheme for two-dimensional hyperbolic conservation laws: A deep learning approach for learning smoothness indicators. CoRR abs/2309.10117 (2023) - 2022
- [j8]Ameya D. Jagtap, Yeonjong Shin, Kenji Kawaguchi, George Em Karniadakis:
Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions. Neurocomputing 468: 165-180 (2022) - [j7]Ameya D. Jagtap, Zhiping Mao, Nikolaus A. Adams, George Em Karniadakis:
Physics-informed neural networks for inverse problems in supersonic flows. J. Comput. Phys. 466: 111402 (2022) - [j6]Zheyuan Hu, Ameya D. Jagtap, George Em Karniadakis, Kenji Kawaguchi:
When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization? SIAM J. Sci. Comput. 44(5): 3158- (2022) - [j5]Khemraj Shukla, Ameya D. Jagtap, James L. Blackshire, Daniel Sparkman, George Em Karniadakis:
A Physics-Informed Neural Network for Quantifying the Microstructural Properties of Polycrystalline Nickel Using Ultrasound Data: A promising approach for solving inverse problems. IEEE Signal Process. Mag. 39(1): 68-77 (2022) - [i9]Ameya D. Jagtap, Dimitrios Mitsotakis, George Em Karniadakis:
Deep learning of inverse water waves problems using multi-fidelity data: Application to Serre-Green-Naghdi equations. CoRR abs/2202.02899 (2022) - [i8]Ameya D. Jagtap, Zhiping Mao, Nikolaus A. Adams, George Em Karniadakis:
Physics-informed neural networks for inverse problems in supersonic flows. CoRR abs/2202.11821 (2022) - [i7]Tim De Ryck, Ameya D. Jagtap, Siddhartha Mishra:
Error estimates for physics informed neural networks approximating the Navier-Stokes equations. CoRR abs/2203.09346 (2022) - [i6]Ameya D. Jagtap, George Em Karniadakis:
How important are activation functions in regression and classification? A survey, performance comparison, and future directions. CoRR abs/2209.02681 (2022) - [i5]Zheyuan Hu, Ameya D. Jagtap, George Em Karniadakis, Kenji Kawaguchi:
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology. CoRR abs/2211.08939 (2022) - 2021
- [j4]Khemraj Shukla, Ameya D. Jagtap, George Em Karniadakis:
Parallel physics-informed neural networks via domain decomposition. J. Comput. Phys. 447: 110683 (2021) - [c1]Ameya D. Jagtap, George E. Karniadakis:
Extended Physics-informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition based Deep Learning Framework for Nonlinear Partial Differential Equations. AAAI Spring Symposium: MLPS 2021 - [i4]Khemraj Shukla, Ameya D. Jagtap, George Em Karniadakis:
Parallel Physics-Informed Neural Networks via Domain Decomposition. CoRR abs/2104.10013 (2021) - [i3]Ameya D. Jagtap, Yeonjong Shin, Kenji Kawaguchi, George Em Karniadakis:
Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions. CoRR abs/2105.09513 (2021) - [i2]Zheyuan Hu, Ameya D. Jagtap, George Em Karniadakis, Kenji Kawaguchi:
When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization? CoRR abs/2109.09444 (2021) - 2020
- [j3]Samala Rathan, Rakesh Kumar, Ameya D. Jagtap:
L1-type smoothness indicators based WENO scheme for nonlinear degenerate parabolic equations. Appl. Math. Comput. 375: 125112 (2020) - [j2]Ameya D. Jagtap, Kenji Kawaguchi, George Em Karniadakis:
Adaptive activation functions accelerate convergence in deep and physics-informed neural networks. J. Comput. Phys. 404 (2020)
2010 – 2019
- 2019
- [i1]Ameya D. Jagtap, Kenji Kawaguchi, George E. Karniadakis:
Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks. CoRR abs/1909.12228 (2019) - 2018
- [j1]Ameya D. Jagtap, A. S. Vasudeva Murthy:
Higher order scheme for two-dimensional inhomogeneous sine-Gordon equation with impulsive forcing. Commun. Nonlinear Sci. Numer. Simul. 64: 178-197 (2018)
Coauthor Index
aka: George E. Karniadakis
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:23 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
