Input Convex Neural Networks

22 September 2016

J. Zico Kolter

Papers citing "Input Convex Neural Networks"

50 / 107 papers shown

Title
On the Depth of Monotone ReLU Neural Networks and ICNNs Egor Bakaev Florestan Brunck Christoph Hertrich Daniel Reichman Amir Yehudayoff 26 0 0 09 May 2025
EquiNO: A Physics-Informed Neural Operator for Multiscale Simulations Hamidreza Eivazi Jendrik-Alexander Tröger Stefan H. A. Wittek Stefan Hartmann Andreas Rausch AI4CE 43 0 0 27 Mar 2025
Input convex neural networks: universal approximation theorem and implementation for isotropic polyconvex hyperelastic energies Gian-Luca Geuken P. Kurzeja David Wiedemann J. Mosler 46 1 0 12 Feb 2025
Learning Exactly Linearizable Deep Dynamics Models R. Moriyasu Masayuki Kusunoki Kenji Kashima AI4CE 62 1 0 28 Jan 2025
Gradient Networks Shreyas Chaudhari Srinivasa Pranav J. M. F. Moura 50 0 0 28 Jan 2025
Non-geodesically-convex optimization in the Wasserstein space Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Petrus Mikkola Marcelo Hartmann Kai Puolamaki Arto Klami 53 2 0 08 Jan 2025
Fast and scalable Wasserstein-1 neural optimal transport solver for single-cell perturbation prediction Yanshuo Chen Zhengmian Hu Wei Chen Heng Huang OT 47 1 0 01 Nov 2024
Stein's method for marginals on large graphical models Tiangang Cui Shuigen Liu X. Tong 43 0 0 15 Oct 2024
Deep Generative Quantile Bayes Jungeum Kim Percy S. Zhai Veronika Rockova 46 0 0 10 Oct 2024
Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport Milena Gazdieva Jaemoo Choi Alexander Kolesov Jaewoong Choi Petr Mokrov Alexander Korotin OT 44 0 0 04 Oct 2024
Improving Neural Optimal Transport via Displacement Interpolation Jaemoo Choi Yongxin Chen Jaewoong Choi OT 43 0 0 03 Oct 2024
Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold Lazar Atanackovic Xi Zhang Brandon Amos Mathieu Blanchette Leo J. Lee Yoshua Bengio Alexander Tong Kirill Neklyudov 33 5 0 26 Aug 2024
JacNet: Learning Functions with Structured Jacobians Jonathan Lorraine Safwan Hossain 42 6 0 23 Aug 2024
Accounting for plasticity: An extension of inelastic Constitutive Artificial Neural Networks Birte Boes Jaan-Willem Simon H. Holthusen AI4CE 34 6 0 27 Jul 2024
Graph Neural Networks Gone Hogwild Olga Solodova Nick Richardson Deniz Oktay Ryan P. Adams AI4CE GNN 21 1 0 29 Jun 2024
Neural Approximate Mirror Maps for Constrained Diffusion Models Berthy T. Feng Ricardo Baptista Katherine L. Bouman MedIm DiffM 48 3 0 18 Jun 2024
Learning Stable and Passive Neural Differential Equations Jing Cheng Ruigang Wang I. Manchester 29 3 0 19 Apr 2024
Globally Stable Neural Imitation Policies Amin Abyaneh Mariana Sosa Guzmán Hsiu-Chin Lin 43 2 0 07 Mar 2024
State-Constrained Zero-Sum Differential Games with One-Sided Information Mukesh Ghimire Lei Zhang Zhenni Xu Yi Ren 36 2 0 05 Mar 2024
On a Neural Implementation of Brenier's Polar Factorization Nina Vesseron Marco Cuturi 41 2 0 05 Mar 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 24 5 0 02 Feb 2024
Admission Prediction in Undergraduate Applications: an Interpretable Deep Learning Approach Amisha Priyadarshini Barbara Martinez Neda Sergio Gago Masagué FAtt 19 1 0 22 Jan 2024
Input Convex Lipschitz RNN: A Fast and Robust Approach for Engineering Tasks Zihao Wang Zhen Wu 18 3 0 15 Jan 2024
What's in a Prior? Learned Proximal Networks for Inverse Problems Zhenghan Fang Sam Buchanan Jeremias Sulam 31 11 0 22 Oct 2023
Nonlinear Filtering with Brenier Optimal Transport Maps Mohammad Al-Jarrah Niyizhen Jin Bamdad Hosseini Amirhossein Taghvaei 27 2 0 21 Oct 2023
A Computational Framework for Solving Wasserstein Lagrangian Flows Kirill Neklyudov Rob Brekelmans Alexander Tong Lazar Atanackovic Qiang Liu Alireza Makhzani OT 34 17 0 16 Oct 2023
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs Alexander Kolesov Petr Mokrov Igor Udovichenko Milena Gazdieva G. Pammer Anastasis Kratsios Evgeny Burnaev Alexander Korotin OT 37 2 0 02 Oct 2023
An adaptively inexact first-order method for bilevel optimization with application to hyperparameter learning Mohammad Salehi Subhadip Mukherjee Lindon Roberts Matthias Joachim Ehrhardt 24 5 0 19 Aug 2023
Decorrelation using Optimal Transport M. Algren J. A. Raine T. Golling OT 26 1 0 11 Jul 2023
Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport Jaemoo Choi Jaewoong Choi Myung-joo Kang OT 23 19 0 24 May 2023
Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks with Soft-Thresholding Chunyan Xiong Meng Lu Xiaotong Yu JIAN-PENG Cao Zhong Chen D. Guo X. Qu MLT 35 0 0 14 Apr 2023
Meta-Learning Parameterized First-Order Optimizers using Differentiable Convex Optimization Tanmay Gautam Samuel Pfrommer Somayeh Sojoudi 18 2 0 29 Mar 2023
PAD: Towards Principled Adversarial Malware Detection Against Evasion Attacks Deqiang Li Shicheng Cui Yun Li Jia Xu Fu Xiao Shouhuai Xu AAML 48 17 0 22 Feb 2023
Interval Type-2 Fuzzy Neural Networks for Multi-Label Classification Dayong Tian Fei Li Yiwen Wei 34 0 0 21 Feb 2023
The Monge Gap: A Regularizer to Learn All Transport Maps Théo Uscidda Marco Cuturi OT 50 26 0 09 Feb 2023
Efficient Gradient Approximation Method for Constrained Bilevel Optimization Siyuan Xu Minghui Zhu 19 19 0 03 Feb 2023
Self-Consistent Velocity Matching of Probability Flows Lingxiao Li Samuel Hurault Justin Solomon 24 11 0 31 Jan 2023
LegendreTron: Uprising Proper Multiclass Loss Learning Kevin Lam Christian J. Walder S. Penev Richard Nock 38 0 0 27 Jan 2023
Rigid Body Flows for Sampling Molecular Crystal Structures Jonas Köhler Michele Invernizzi P. D. Haan Frank Noé AI4CE 35 27 0 26 Jan 2023
Learning Gradients of Convex Functions with Monotone Gradient Networks Shreyas Chaudhari Srinivasa Pranav J. M. F. Moura 9 6 0 25 Jan 2023
Analyzing Inexact Hypergradients for Bilevel Learning Matthias Joachim Ehrhardt Lindon Roberts 24 8 0 11 Jan 2023
Regularized Optimal Transport Layers for Generalized Global Pooling Operations Hongteng Xu Minjie Cheng 36 4 0 13 Dec 2022
A Neural-Network-Based Convex Regularizer for Inverse Problems Alexis Goujon Sebastian Neumayer Pakshal Bohra Stanislas Ducotterd M. Unser 13 26 0 22 Nov 2022
Equivariance with Learned Canonicalization Functions Sekouba Kaba Arnab Kumar Mondal Yan Zhang Yoshua Bengio Siamak Ravanbakhsh 36 61 0 11 Nov 2022
CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks Xuan Rao Bo Zhao Xiaosong Yi 74 4 0 11 Nov 2022
Entropic Neural Optimal Transport via Diffusion Processes Nikita Gushchin Alexander Kolesov Alexander Korotin Dmitry Vetrov Evgeny Burnaev OT DiffM 35 36 0 02 Nov 2022
Non-Linear Coordination Graphs Yipeng Kang Tonghan Wang Xiao-Ren Wu Qianlan Yang Chongjie Zhang 29 9 0 26 Oct 2022
Proximal Mean Field Learning in Shallow Neural Networks Alexis M. H. Teter Iman Nodozi A. Halder FedML 40 1 0 25 Oct 2022
Neural Conservation Laws: A Divergence-Free Perspective Jack Richter-Powell Y. Lipman Ricky T. Q. Chen 46 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 28 6 0 22 Sep 2022