Differentiable Optimization

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6 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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Latest papers 58

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Learning Multi-Agent Coordination via Sheaf-ADMM
May 29, 2026Jeffrey Seely, Bartłomiej Cupiał, Llion JonesMulti-Agent System Optimization Multi-Agent Coordination
Sakana AI, Tokyo, Japan · University of Warsaw · AKCES NCBR
DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers
May 28, 2026Shraman Pal, Can LiDifferentiable Optimization Neurosymbolic Learning
Davidson School of Chemical Engineering, Purdue University, West Lafayette, USA.
Semiparametric Efficient Bilevel Gradient Estimation
May 20, 2026Fares El Khoury, Houssam Zenati, Nathan Kallus +2Semiparametric Inference Bilevel Optimization
Université Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK · Gatsby Computational Neuroscience Unit, University College London · Cornell University +1
An End-to-End PyTorch Interface for Differentiable PDE Solvers: A RANS Model-Correction Study
May 19, 2026Luca Saverio, Michele Alessandro Bucci, Gianmarco Farro +2PDE Solving Differentiable Optimization
MONHADE · Digital Sciences & Technologies Department, Safran Tech, Magny-Les-Hameaux, 78114, France. · DAAA, ONERA, Institut Polytechnique de Paris, Meudon, 92190, France. +1
Financially Guided Deep Portfolio Optimization
May 16, 2026Rahul Fernandes, Travis DesellQuantitative Finance Portfolio Optimization
Department of Software Engineering Rochester Institute of Technology Rochester, New York, USA
Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning
May 16, 2026David Troxell, Noah Roemer, Guido MontúfarDeep Learning Optimization Algorithmic Fairness
Department of Statistics & Data Science, University of California, Los Angeles, USA · Department of Mathematics, University of California, Los Angeles, USA · Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
Neural QAOA $^{2}$ : Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization
May 13, 2026Zubin Zheng, Jiahao Wu, Shengcai LiuQuadratic Unconstrained Binary Optimization Differentiable Optimization
Guangdong Provincial Key Labora- tory of Brain-Inspired Intelligent Computation, Department of CSE, SUSTech.
WildPose: A Unified Framework for Robust Pose Estimation in the Wild
May 12, 2026Jianhao Zheng, Liyuan Zhu, Zihan Zhu +1Camera Pose Estimation Visual SLAM
1Stanford University · 2ETH Zürich
Vector Scaffolding: Inter-Scale Orchestration for Differentiable Image Vectorization
May 12, 2026Jaerin Lee, Kanggeon Lee, Kyoung Mu LeeDifferentiable Rendering Differentiable Optimization
Dept. of ECE&ASRI, Seoul National University, Korea · IPAI, Seoul National University, Korea
Select-then-differentiate: Solving Bilevel Optimization with Manifold Lower-level Solution Sets
May 9, 2026Saeed Masiha, Zebang Shen, Negar Kiyavash +1Nonconvex Optimization Bilevel Optimization
EPFL School of Management of Technology, Station 5, 1015 Lausanne, Switzerland · ETH Department of Computer Science, Universitätstrasse 6, 8092 Zürich, Switzerland
Approximation-Free Differentiable Oblique Decision Trees
May 8, 2026Subrat Prasad Panda, Blaise Genest, Arvind EaswaranInterpretable ML Tabular ML
College of Computing and Data Science Nanyang Technological University Singapore
SNAPO: Smooth Neural Adjoint Policy Optimization for Optimal Control via Differentiable Simulation
May 7, 2026Dmitri Goloubentsev, Natalija KarpichinaPolicy Optimization Differentiable Programming
MatLogica, U.K.
CredibleDFGO: Differentiable Factor Graph Optimization with Credibility Supervision
May 7, 2026Liang Qian, Penggao Yan, Penghui Xu +1Factor Graph Optimization Wireless Localization
Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University, Hong Kong, China
InkDiffuser: High-Fidelity One-shot Chinese Calligraphy via Differentiable Morphological Optimization
May 7, 2026Kunchong Shi, Jing ZhangImage Generation Diffusion-Based Image Generation
Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, 200237 China
Differentiable Parameter Optimization for DAEs with State-Dependent Events
May 6, 2026Ion Matei, Maksym Zhenirovskyy, Anthony WongDynamical Systems Automatic Differentiation
Fujitsu Research of America
Graph Normalization: Fast Binarizing Dynamics for Differentiable MWIS
May 6, 2026Laurent GuiguesDynamical Systems Replicator Dynamics
Geometry-Aware Neural Optimizer for Shape Optimization and Inversion
May 6, 2026Guoze Sun, Tianya Miao, Haoyang Huang +4Neural Surrogate Modeling Geometric Representation Learning
Gaoling School of Artificial Intelligence, Renmin University of China
Differentiable Optimization Layered Safety-Critical Control for Risk-Aware Navigation via Conformal Prediction
May 5, 2026Jinyang Dong, Shizhen Wu, Yongchun FangSafety-Critical Control Control Barrier Functions
Institute of Robotics and Automatic Information Systems, College of Artificial Intelligence, Nankai University, Tianjin 300071, China · Academy for Advanced Interdisciplinary Studies, Nankai University, Tianjin 300071, China · Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China
Exact Higher-Order Derivatives for SE(3) via Analytical/AD Methods
May 4, 2026Frank O. KuehnelAutomatic Differentiation Lie Group Methods
Sigma Point Labs, Denver, CO, USA
Decision-Focused Learning via Tangent-Space Projection of Prediction Error
May 2, 2026Junhyeong Lee, Sangjin Jin, Yongjae LeeDecision-Focused Learning Differentiable Optimization
Department of Industrial Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea.
Differentiable Multiphysics Co-Optimization via Implicit Neural Representations: A Transient Hamburger-Cooking Benchmark
May 1, 2026Navid ZobeiryDifferentiable Optimization Multi-Objective Optimization
Department of Materials Science and Engineering, University of Washington · William E. Boeing Department of Aeronautics & Astronautics, University of Washington, Seattle, WA 98195, USA
NLPOpt-Net: A Learning Method for Nonlinear Optimization with Feasibility Guarantees
Apr 30, 2026Bimol Nath Roy, Rahul Golder, MM Faruque HasanNeural Network Optimization Learning to Optimize
Texas A&M University
Differentiable Satellite Constellation Configuration via Relaxed Coverage and Revisit Objectives
Apr 21, 2026Shreeyam Kacker, Kerri CahoyDifferentiable Programming Differentiable Optimization
Department of Aeronautics and Astronautics MIT
MetaTune: Adjoint-based Meta-tuning via Robotic Differentiable Dynamics
Mar 28, 2026Xiexin Peng, Bingheng Wang, Tao Zhang +2Robust Control Feedback Control
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China · Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore · Wuhan Zhenyou Technology Co., Ltd., Wuhan 430205, China
Shiva-DiT: Residual-Based Differentiable Top- $k$ Selection for Efficient Diffusion Transformers
Feb 5, 2026Jiaji Zhang, Hailiang Zhao, Jiaju Wu +3Diffusion Model Acceleration Diffusion Transformer
College of Computer Science and Technology, Zhejiang University · 3Nanyang Technological University
Learning to Optimize by Differentiable Programming
Jan 23, 2026Liping Tao, Xindi Tong, Chee Wei TanPrimal-Dual Optimization Learning to Optimize
Nanyang Technological University, Singapore · Nanyang Technological University, Singapore, Singapore
Learning to bin: differentiable and Bayesian optimization for multi-dimensional discriminants in high-energy physics
Jan 12, 2026Johannes Erdmann, Nitish Kumar Kasaraguppe, Florian MausolfHigh-Energy Physics Differentiable Optimization
RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany
Differentiable Expectation-Maximisation and Applications to Gaussian Mixture Model Optimal Transport
Sep 2, 2025Samuel Boïté, Eloi Tanguy, Julie Delon +2Gaussian Mixture Models Expectation-Maximization
Université Paris Cité, CNRS, MAP5, F-75006 Paris, France · Centre Borelli, CNRS and ENS Paris-Saclay, F-91190 Gif-sur-Yvette, France · CMAP, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris

May 29, 2026, cs.LGJ/K move · Enter open · S save

Learning Multi-Agent Coordination via Sheaf-ADMM

Jeffrey Seely, Bartłomiej Cupiał, Llion Jones

Sakana AI, Tokyo, Japan · University of Warsaw · AKCES NCBR

Multi-Agent System Optimization Multi-Agent Coordination Alternating Direction Method of Multipliers Multi-Agent Consensus Differentiable Optimization

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We present a differentiable optimization framework for multi-agent coordination. An input is decomposed into overlapping local views, each processed by an agent that solves a convex subproblem parameterized by a neural encoder. Agents coordinate through the Alternating Direction Method of Multipliers (ADMM) with inter-agent constraints specified by a cellular sheaf. The sheaf specifies which aspects of neighboring solutions must agree, allowing for heterogeneous notions of global consensus. Backpropagating through the unrolled optimization jointly trains all components of the multi-agent system. We evaluate on maze pathfinding, image classification, and Sudoku, where agents with individually insufficient local views learn to coordinate to produce correct global outputs. On MNIST, the local-view decomposition yields improved robustness to distribution shifts relative to a standard CNN. On Sudoku, the optimization-derived structure yields markedly higher solve rates than parameter-matched MPNN baselines. Finally, the ADMM structure exposes distinct primal, consensus, and dual state variables, opening the coordination dynamics to direct analysis and intervention -- a property unavailable in standard message-passing architectures.

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