Fashionable Modelling with Flux

1 November 2018

Marco Concetto Rudilosso

Papers citing "Fashionable Modelling with Flux"

50 / 59 papers shown

Title
What You See is Not What You Get: Neural Partial Differential Equations and The Illusion of Learning Arvind Mohan Ashesh Chattopadhyay Jonah Miller 94 0 0 22 Nov 2024
Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions Christian Nauck R. Gorantla M. Lindner Konstantin Schurholt Antonia S. J. S. Mey Frank Hellmann AI4CE 42 2 0 17 Jul 2024
ProDAG: Projection-Induced Variational Inference for Directed Acyclic Graphs Ryan Thompson Edwin V. Bonilla Robert Kohn 40 0 0 24 May 2024
Dual Lagrangian Learning for Conic Optimization Mathieu Tanneau Pascal Van Hentenryck 21 4 0 05 Feb 2024
Deep Learning for Koopman-based Dynamic Movement Primitives Tyler Han Carl Glen Henshaw 30 0 0 06 Dec 2023
Taming Waves: A Physically-Interpretable Machine Learning Framework for Realizable Control of Wave Dynamics Tristan A. Shah Feruza A. Amirkulova Stas Tiomkin AI4CE 21 0 0 27 Nov 2023
Learning Optimal Power Flow Value Functions with Input-Convex Neural Networks Andrew Rosemberg Mathieu Tanneau Bruno Fanzeres Joaquim Garcia Pascal Van Hentenryck 15 3 0 06 Oct 2023
Endogenous Macrodynamics in Algorithmic Recourse Patrick Altmeyer Giovan Angela Aleksander Buszydlik Karol Dobiczek A. V. Deursen Cynthia C. S. Liem 21 7 0 16 Aug 2023
Kernelised Normalising Flows Eshant English Matthias Kirchler C. Lippert TPM 33 0 0 27 Jul 2023
Effective Latent Differential Equation Models via Attention and Multiple Shooting German Abrevaya Mahta Ramezanian-Panahi Jean-Christophe Gagnon-Audet Pablo Polosecki Irina Rish S. Dawson Guillermo Cecchi G. Dumas MedIm 21 1 0 11 Jul 2023
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints Alistair J R White Niki Kilbertus Maximilian Gelbrecht Niklas Boers 20 6 0 16 Jun 2023
Chemellia: An Ecosystem for Atomistic Scientific Machine Learning Anant Thazhemadam Dhairya Gandhi V. Viswanathan Rachel C. Kurchin 13 0 0 19 May 2023
Random Function Descent Felix Benning L. Döring 13 0 0 02 May 2023
Learned multiphysics inversion with differentiable programming and machine learning M. Louboutin Ziyi Yin Rafael Orozco Thomas J. Grady Ali Siahkoohi G. Rizzuti Philipp A. Witte O. Møyner Gerard Gorman Felix J. Herrmann AI4CE 26 10 0 12 Apr 2023
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study Robert Ferrando Laurent Pagnier R. Mieth Zhirui Liang Y. Dvorkin D. Bienstock Michael Chertkov 26 7 0 31 Mar 2023
Kernel interpolation of acoustic transfer functions with adaptive kernel for directed and residual reverberations Juliano G. C. Ribeiro Shoichi Koyama Hiroshi Saruwatari 14 12 0 07 Mar 2023
Analyzing the Performance of Deep Encoder-Decoder Networks as Surrogates for a Diffusion Equation J. Q. Toledo-Marín J. Glazier Geoffrey C. Fox 21 4 0 07 Feb 2023
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks Ryan Thompson Amir Dezfouli Robert Kohn 31 4 0 02 Feb 2023
MLPGradientFlow: going with the flow of multilayer perceptrons (and finding minima fast and accurately) Johanni Brea Flavio Martinelli Berfin Simsek W. Gerstner 23 3 0 25 Jan 2023
Global Performance Guarantees for Neural Network Models of AC Power Flow Samuel C. Chevalier Spyros Chatzivasileiadis 10 6 0 14 Nov 2022
Bridging HPC Communities through the Julia Programming Language Valentin Churavy William F. Godoy Carsten Bauer Hendrik Ranocha Michael Schlottke-Lakemper ... Mosè Giordano E. Schnetter Samuel Omlin Jeffrey S. Vetter Alan Edelman 25 10 0 04 Nov 2022
Learning Modular Simulations for Homogeneous Systems Jayesh K. Gupta Sai H. Vemprala Ashish Kapoor 19 6 0 28 Oct 2022
Calibration tests beyond classification David Widmann Fredrik Lindsten Dave Zachariah 27 17 0 21 Oct 2022
Training neural network ensembles via trajectory sampling Jamie F. Mair Dominic C. Rose J. P. Garrahan 13 2 0 22 Sep 2022
Recursive Neural Programs: Variational Learning of Image Grammars and Part-Whole Hierarchies Ares Fisher Rajesh P. N. Rao GAN DRL 16 2 0 16 Jun 2022
Fast Conditional Network Compression Using Bayesian HyperNetworks Phuoc Nguyen T. Tran Ky Le Sunil R. Gupta Santu Rana Dang Nguyen Trong Nguyen S. Ryan Svetha Venkatesh BDL 28 6 0 13 May 2022
Machines of finite depth: towards a formalization of neural networks Pietro Vertechi M. Bergomi PINN 16 2 0 27 Apr 2022
Machine Learning and Deep Learning -- A review for Ecologists Maximilian Pichler F. Hartig 36 124 0 11 Apr 2022
STEADY: Simultaneous State Estimation and Dynamics Learning from Indirect Observations Jiayi Wei Jarrett Holtz Işıl Dillig Joydeep Biswas 26 4 0 02 Mar 2022
Deep learning and differential equations for modeling changes in individual-level latent dynamics between observation periods G. Köber R. Kalisch Lara Puhlmann A. Chmitorz Anita Schick Harald Binder 18 1 0 15 Feb 2022
SAFE-OCC: A Novelty Detection Framework for Convolutional Neural Network Sensors and its Application in Process Control J. Pulsipher Luke D. J. Coutinho Tyler A. Soderstrom Victor M. Zavala HAI 12 7 0 03 Feb 2022
Machine Learning Kreuzer--Skarke Calabi--Yau Threefolds Per Berglund Ben Campbell Vishnu Jejjala 42 20 0 16 Dec 2021
Multicriteria interpretability driven Deep Learning M. Repetto 19 13 0 28 Nov 2021
Equinox: neural networks in JAX via callable PyTrees and filtered transformations Patrick Kidger Cristian Garcia 11 115 0 30 Oct 2021
Physics informed machine learning with Smoothed Particle Hydrodynamics: Hierarchy of reduced Lagrangian models of turbulence M. Woodward Yifeng Tian Criston Hyett Chris L. Fryer Daniel Livescu Mikhail Stepanov Michael Chertkov AI4CE 13 7 0 25 Oct 2021
Multiple shooting for training neural differential equations on time series Evren Mert Turan J. Jäschke AI4TS 37 23 0 14 Sep 2021
Low-memory stochastic backpropagation with multi-channel randomized trace estimation M. Louboutin Ali Siahkoohi Rongrong Wang Felix J. Herrmann 16 0 0 13 Jun 2021
Parameter Inference with Bifurcation Diagrams Gregory Szép Neil Dalchau A. Csikász-Nagy 11 4 0 08 Jun 2021
Optimal Transport Based Refinement of Physics-Informed Neural Networks Vaishnav Tadiparthi R. Bhattacharya OT 10 2 0 26 May 2021
Chameleon: A Semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEs Johannes Otterbach Thomas Wollmann 15 1 0 08 May 2021
EBIC.JL -- an Efficient Implementation of Evolutionary Biclustering Algorithm in Julia Pawel Renc Patryk Orzechowski A. Byrski Jarosław Wąs J. Moore 24 4 0 03 May 2021
Mapping the Internet: Modelling Entity Interactions in Complex Heterogeneous Networks Šimon Mandlík Tomás Pevný 13 5 0 19 Apr 2021
SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning Félix Chalumeau Ilan Coulon Quentin Cappart Louis-Martin Rousseau 36 21 0 18 Feb 2021
Deep learning approaches to surrogates for solving the diffusion equation for mechanistic real-world simulations J. Q. Toledo-Marín Geoffrey C. Fox J. Sluka J. Glazier MedIm AI4CE 19 8 0 10 Feb 2021
Optimal Energy Shaping via Neural Approximators Stefano Massaroli Michael Poli Federico Califano Jinkyoo Park Atsushi Yamashita Hajime Asama 16 12 0 14 Jan 2021
Using Differentiable Programming for Flexible Statistical Modeling Maren Hackenberg M. Grodd Clemens Kreutz Martina Fischer J. Esins L. Grabenhenrich C. Karagiannidis Harald Binder 18 4 0 07 Dec 2020
Discovery of the Hidden State in Ionic Models Using a Domain-Specific Recurrent Neural Network Shahriar Iravanian 20 0 0 14 Nov 2020
Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics Li Li Stephan Hoyer Ryan Pederson Ruoxi Sun E. D. Cubuk Patrick F. Riley K. Burke AI4CE 21 120 0 17 Sep 2020
Augmenting Neural Differential Equations to Model Unknown Dynamical Systems with Incomplete State Information Robert Strauss 16 3 0 19 Aug 2020
Supervised Whole DAG Causal Discovery Hebi Li Qi Xiao Jin Tian CML 19 17 0 08 Jun 2020