Input Convex Neural Networks

22 September 2016

J. Zico Kolter

Papers citing "Input Convex Neural Networks"

50 / 112 papers shown

Title
Neural Conservation Laws: A Divergence-Free Perspective Jack Richter-Powell Y. Lipman Ricky T. Q. Chen 48 50 0 04 Oct 2022
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows G. Morel Lucas Drumetz Simon Benaïchouche Nicolas Courty F. Rousseau OT 30 6 0 22 Sep 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 25 22 0 26 Jul 2022
Learning differentiable solvers for systems with hard constraints Geoffrey Negiar Michael W. Mahoney Aditi S. Krishnapriyan 26 28 0 18 Jul 2022
Landscape Learning for Neural Network Inversion Ruoshi Liu Chen-Guang Mao Purva Tendulkar Hongya Wang Carl Vondrick 32 8 0 17 Jun 2022
Dual Convexified Convolutional Neural Networks Site Bai Chuyang Ke Jean Honorio 24 1 0 27 May 2022
Neural Lyapunov Differentiable Predictive Control Sayak Mukherjee Ján Drgoňa Aaron Tuor M. Halappanavar D. Vrabie 37 13 0 22 May 2022
NN-EUCLID: deep-learning hyperelasticity without stress data Prakash Thakolkaran Akshay Joshi Yiwen Zheng Moritz Flaschel L. Lorenzis Siddhant Kumar 24 98 0 04 May 2022
An Optimal Transport Formulation of Bayes' Law for Nonlinear Filtering Algorithms Amirhossein Taghvaei Bamdad Hosseini OT 34 17 0 22 Mar 2022
Learning Stabilizable Deep Dynamics Models Kenji Kashima Ryota Yoshiuchi Yutaka Kawano 19 4 0 18 Mar 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview Zhijie Chen Mingquan Feng Junchi Yan H. Zha AI4CE 19 15 0 28 Feb 2022
Equilibrium Aggregation: Encoding Sets via Optimization Sergey Bartunov F. Fuchs Timothy Lillicrap 19 7 0 25 Feb 2022
Multivariate Quantile Function Forecaster Kelvin K. Kan Franccois-Xavier Aubet Tim Januschowski Youngsuk Park Konstantinos Benidis Lars Ruthotto Jan Gasthaus AI4TS 39 22 0 23 Feb 2022
Global Optimization Networks Sen Zhao Erez Louidor Ilan Oleksandr Mangylov Maya R. Gupta 18 5 0 02 Feb 2022
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions Aaron Mishkin Arda Sahiner Mert Pilanci OffRL 77 30 0 02 Feb 2022
Tutorial on amortized optimization Brandon Amos OffRL 75 43 0 01 Feb 2022
Wasserstein Iterative Networks for Barycenter Estimation Alexander Korotin Vage Egiazarian Lingxiao Li Evgeny Burnaev 29 24 0 28 Jan 2022
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 72 54 0 04 Dec 2021
Input Convex Gradient Networks Jack Richter-Powell Jonathan Lorraine Brandon Amos 12 15 0 23 Nov 2021
Physics-informed linear regression is competitive with two Machine Learning methods in residential building MPC Felix Bünning B. Huber Adrian Schalbetter Ahmed Aboudonia Mathias Hudoba de Badyn Philipp Heer Roy S. Smith John Lygeros AI4CE 14 65 0 29 Oct 2021
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems Andreas Schlaginhaufen Philippe Wenk Andreas Krause Florian Dorfler 27 15 0 27 Oct 2021
Efficient Gradient Flows in Sliced-Wasserstein Space Clément Bonet Nicolas Courty Franccois Septier Lucas Drumetz 31 21 0 21 Oct 2021
Continuous Control with Action Quantization from Demonstrations Robert Dadashi Léonard Hussenot Damien Vincent Sertan Girgin Anton Raichuk M. Geist Olivier Pietquin OffRL 26 23 0 19 Oct 2021
Offline Reinforcement Learning for Autonomous Driving with Safety and Exploration Enhancement Tianyu Shi Dong Chen Kaian Chen Zhaojian Li OffRL 18 31 0 13 Oct 2021
Solving the Dirichlet problem for the Monge-Ampère equation using neural networks K. Nystrom Matias Vestberg 31 2 0 07 Oct 2021
Generative Modeling with Optimal Transport Maps Litu Rout Alexander Korotin Evgeny Burnaev OT DiffM 122 65 0 06 Oct 2021
Optimization with Constraint Learning: A Framework and Survey Adejuyigbe O. Fajemisin Donato Maragno D. Hertog 58 46 0 05 Oct 2021
Data-driven Tissue Mechanics with Polyconvex Neural Ordinary Differential Equations Vahidullah Tac F. Sahli Costabal A. B. Tepole AI4CE 44 69 0 03 Oct 2021
Learning Energy-Based Approximate Inference Networks for Structured Applications in NLP Lifu Tu BDL 35 0 0 27 Aug 2021
Polyconvex anisotropic hyperelasticity with neural networks Dominik K. Klein Mauricio Fernández Robert J. Martin P. Neff Oliver Weeger 33 151 0 20 Jun 2021
Riemannian Convex Potential Maps Samuel N. Cohen Brandon Amos Y. Lipman 18 22 0 18 Jun 2021
Proximal Optimal Transport Modeling of Population Dynamics Charlotte Bunne Laetitia Meng-Papaxanthos Andreas Krause Marco Cuturi OT 43 81 0 11 Jun 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 40 52 0 01 Jun 2021
Learning Deep Energy Shaping Policies for Stability-Guaranteed Manipulation S. A. Khader Hang Yin Pietro Falco Danica Kragic 8 12 0 30 Mar 2021
Almost Surely Stable Deep Dynamics Nathan P. Lawrence Philip D. Loewen M. Forbes Johan U. Backstrom R. Bhushan Gopaluni BDL 32 20 0 26 Mar 2021
Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction Hongyao Tang Jianye Hao Guangyong Chen Pengfei Chen C. L. P. Chen Yaodong Yang Lu Zhang Wulong Liu Zhaopeng Meng OffRL 27 4 0 03 Mar 2021
Data-Driven Random Access Optimization in Multi-Cell IoT Networks with NOMA Sami Khairy Prasanna Balaprakash L. Cai H. Vincent Poor 24 6 0 02 Jan 2021
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 119 95 0 10 Dec 2020
Input Convex Neural Networks for Building MPC Felix Bünning Adrian Schalbetter Ahmed Aboudonia Mathias Hudoba de Badyn Philipp Heer John Lygeros 20 39 0 26 Nov 2020
State space models for building control: how deep should you go? B. Schubnel R. Carrillo Paolo Taddeo L. C. Casals J. Salom Y. Stauffer P. Alet 17 14 0 23 Oct 2020
Reinforcement Learning with Combinatorial Actions: An Application to Vehicle Routing A. Delarue Ross Anderson Christian Tjandraatmadja 19 92 0 22 Oct 2020
$f$ -GAIL: Learning $f$ -Divergence for Generative Adversarial Imitation Learning Xin Zhang Yanhua Li Ziming Zhang Zhi-Li Zhang 21 31 0 02 Oct 2020
Learning Thermodynamically Stable and Galilean Invariant Partial Differential Equations for Non-equilibrium Flows Juntao Huang Zhiting Ma Y. Zhou W. Yong AI4CE 30 16 0 28 Sep 2020
Sampling-based Reachability Analysis: A Random Set Theory Approach with Adversarial Sampling T. Lew Marco Pavone AAML 17 53 0 24 Aug 2020
Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks JiaoJiao Fan Amirhossein Taghvaei Yongxin Chen 34 56 0 08 Jul 2020
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems Kai Wang Bryan Wilder Andrew Perrault Milind Tambe 21 28 0 18 Jun 2020
Counterexample-Guided Learning of Monotonic Neural Networks Aishwarya Sivaraman G. Farnadi T. Millstein Guy Van den Broeck 24 50 0 16 Jun 2020
The Curious Case of Convex Neural Networks S. Sivaprasad Ankur Singh Naresh Manwani Vineet Gandhi 37 26 0 09 Jun 2020
Deep Learning and Knowledge-Based Methods for Computer Aided Molecular Design -- Toward a Unified Approach: State-of-the-Art and Future Directions Abdulelah S. Alshehri R. Gani Fengqi You AI4CE 30 83 0 18 May 2020
Physarum Powered Differentiable Linear Programming Layers and Applications Zihang Meng Sathya Ravi Vikas Singh 19 5 0 30 Apr 2020