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Ranjan Anantharaman
Ranjan Anantharaman
JuliaHub Inc.
Geverifieerd e-mailadres voor mit.edu
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Circuit‐theory applications to connectivity science and conservation
BG Dickson, CM Albano, R Anantharaman, P Beier, J Fargione, ...
Conservation biology 33 (2), 239-249, 2019
2812019
Circuitscape in Julia: High performance connectivity modelling to support conservation decisions
R Anantharaman, K Hall, V Shah, A Edelman
arXiv preprint arXiv:1906.03542, 2019
1032019
Modelingtoolkit: A composable graph transformation system for equation-based modeling
Y Ma, S Gowda, R Anantharaman, C Laughman, V Shah, C Rackauckas
arXiv preprint arXiv:2103.05244, 2021
752021
Circuitscape in julia: empowering dynamic approaches to connectivity assessment
KR Hall, R Anantharaman, VA Landau, M Clark, BG Dickson, A Jones, ...
Land 10 (3), 301, 2021
612021
Omniscape. jl: Software to compute omnidirectional landscape connectivity
VA Landau, VB Shah, R Anantharaman, KR Hall
Journal of Open Source Software 6 (57), 2829, 2021
482021
Accelerating simulation of stiff nonlinear systems using continuous-time echo state networks
R Anantharaman, Y Ma, S Gowda, C Laughman, V Shah, A Edelman, ...
arXiv preprint arXiv:2010.04004, 2020
272020
Composing modeling and simulation with machine learning in Julia
C Rackauckas, M Gwozdz, A Jain, Y Ma, F Martinuzzi, U Rajput, E Saba, ...
2022 Annual Modeling and Simulation Conference (ANNSIM), 1-17, 2022
202022
ModelingToolkit: A composable graph transformation system for equation-based modeling (2021)
Y Ma, S Gowda, R Anantharaman, C Laughman, V Shah, C Rackauckas
arXiv preprint arXiv:2103.05244, 0
11
Continuous-time echo state networks for predicting power system dynamics
C Roberts, JD Lara, R Henriquez-Auba, M Bossart, R Anantharaman, ...
Electric Power Systems Research 212, 108562, 2022
102022
Circuitscape in Julia: High performance connectivity modelling to support conservation decisions. arXiv 2019
R Anantharaman, K Hall, V Shah, A Edelman
arXiv preprint arXiv:1906.03542, 0
7
Stably accelerating stiff quantitative systems pharmacology models: Continuous-time echo state networks as implicit machine learning
R Anantharaman, A Abdelrehim, A Jain, A Pal, D Sharp, A Edelman, ...
IFAC-PapersOnLine 55 (23), 1-6, 2022
52022
Composable and reusable neural surrogates to predict system response of causal model components
R Anantharaman, A Abdelrehim, F Martinuzzi, S Yalburgi, E Saba, ...
AAAI 2022 Workshop on AI for Design and Manufacturing (ADAM), 2021
52021
Approximation of Large Stiff Acausal Models
R Anantharaman
Massachusetts Institute of Technology, 2023
2023
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Artikelen 1–13