Imposing Hard Constraints on Deep Networks: Promises and Limitations

7 June 2017

Papers citing "Imposing Hard Constraints on Deep Networks: Promises and Limitations"

32 / 32 papers shown

Title
Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture Yikun Hou Suvrit Sra A. Yurtsever 39 0 0 28 Jan 2025
TL-PCA: Transfer Learning of Principal Component Analysis Sharon Hendy Yehuda Dar 169 1 0 14 Oct 2024
Class and Region-Adaptive Constraints for Network Calibration Balamurali Murugesan Julio Silva-Rodríguez Ismail Ben Ayed Jose Dolz 41 1 0 19 Mar 2024
RAYEN: Imposition of Hard Convex Constraints on Neural Networks J. Tordesillas Jonathan P. How Marco Hutter 41 12 0 17 Jul 2023
Differentially Private Distributed Convex Optimization Minseok Ryu Kibaek Kim FedML 38 1 0 28 Feb 2023
Constrained Empirical Risk Minimization: Theory and Practice Eric Marcus Ray Sheombarsing Jan-Jakob Sonke Jonas Teuwen 30 1 0 09 Feb 2023
CQnet: convex-geometric interpretation and constraining neural-network trajectories Bas Peters 40 0 0 09 Feb 2023
Hierarchical learning, forecasting coherent spatio-temporal individual and aggregated building loads J. Leprince H. Madsen J. Møller W. Zeiler 35 6 0 30 Jan 2023
Towards Positive Jacobian: Learn to Postprocess Diffeomorphic Image Registration with Matrix Exponential Soumyadeep Pal Matthew Tennant Nilanjan Ray MedIm 26 2 0 01 Feb 2022
Neural network training under semidefinite constraints Patricia Pauli Niklas Funcke Dennis Gramlich Mohamed Amine Msalmi Frank Allgöwer GAN 26 13 0 03 Jan 2022
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 27 65 0 29 Oct 2021
HybridSDF: Combining Deep Implicit Shapes and Geometric Primitives for 3D Shape Representation and Manipulation Subeesh Vasu Nicolas Talabot Artem Lukoianov Pierre Baqué Jonathan Donier Pascal Fua 44 4 0 22 Sep 2021
Characterizing possible failure modes in physics-informed neural networks Aditi S. Krishnapriyan A. Gholami Shandian Zhe Robert M. Kirby Michael W. Mahoney PINN AI4CE 51 618 0 02 Sep 2021
Fast Jacobian-Vector Product for Deep Networks Randall Balestriero Richard Baraniuk 34 4 0 01 Apr 2021
High-level Prior-based Loss Functions for Medical Image Segmentation: A Survey Rosana El Jurdia Caroline Petitjean P. Honeine Veronika Cheplygina F. Abdallah SSeg MedIm 38 79 0 16 Nov 2020
Physics-constrained Deep Learning of Multi-zone Building Thermal Dynamics Ján Drgoňa Aaron Tuor V. Chandan D. Vrabie AI4CE 27 115 0 11 Nov 2020
LCollision: Fast Generation of Collision-Free Human Poses using Learned Non-Penetration Constraints Qingyang Tan Zherong Pan Tianyi Zhou 3DH 32 10 0 06 Nov 2020
Point-to-set distance functions for weakly supervised segmentation Bas Peters 18 1 0 27 Jul 2020
Physics informed deep learning for computational elastodynamics without labeled data Chengping Rao Hao Sun Yang Liu PINN AI4CE 31 222 0 10 Jun 2020
One Size Fits All: Can We Train One Denoiser for All Noise Levels? Abhiram Gnanasambandam Stanley H. Chan OOD 19 21 0 19 May 2020
Lossy Compression with Distortion Constrained Optimization T. V. Rozendaal Guillaume Sautière Taco S. Cohen 31 13 0 08 May 2020
Structure-preserving neural networks Quercus Hernandez Alberto Badías D. González Francisco Chinesta Elías Cueto PINN 30 70 0 09 Apr 2020
Hybrid Classification and Reasoning for Image-based Constraint Solving Maxime Mulamba Jayanta Mandi Rocsildes Canoy Tias Guns 35 11 0 24 Mar 2020
Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling Arka Daw R. Q. Thomas C. Carey J. Read A. Appling Anuj Karpatne AI4CE 39 117 0 06 Nov 2019
Constrained domain adaptation for Image segmentation M. Bateson Jose Dolz H. Kervadec H. Lombaert Ismail Ben Ayed GAN 26 97 0 08 Aug 2019
ART: Abstraction Refinement-Guided Training for Provably Correct Neural Networks Xuankang Lin He Zhu R. Samanta Suresh Jagannathan AAML 27 28 0 17 Jul 2019
Deep Smoothing of the Implied Volatility Surface Damien Ackerer Natasa Tagasovska Thibault Vatter 39 34 0 12 Jun 2019
Design of Communication Systems using Deep Learning: A Variational Inference Perspective Vishnu Raj Sheetal Kalyani 42 22 0 18 Apr 2019
Analytically Embedding Differential Equation Constraints into Least Squares Support Vector Machines using the Theory of Functional Connections Carl Leake Hunter Johnston Lidia Smith D. Mortari 22 23 0 13 Dec 2018
Constrained-CNN losses for weakly supervised segmentation H. Kervadec Jose Dolz Meng Tang Eric Granger Yuri Boykov Ismail Ben Ayed 27 239 0 12 May 2018
Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision Sathya Ravi Tuan Dinh Vishnu Suresh Lokhande Vikas Singh AI4CE 35 22 0 17 Mar 2018
A Semantic Loss Function for Deep Learning with Symbolic Knowledge Jingyi Xu Zilu Zhang Tal Friedman Yitao Liang Guy Van den Broeck 49 446 0 29 Nov 2017