L4DC

Other ML

772 papers · 2020–2026

L4DC (Learning for Dynamics and Control) focuses on the intersection of machine learning, dynamical systems, and control.

Papers per year

104

114

139

120

106

'20

'25

Top authors

Nikolai Matni 14 papers

Yang Zheng 10 papers

Na Li 10 papers

Sebastian Trimpe 10 papers

Sandra Hirche 9 papers

George J. Pappas 9 papers

Rose Yu 9 papers

Alessandro Abate 8 papers

Changliu Liu 8 papers

Karl Henrik Johansson 8 papers

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their counts at this venue are combined. How identity is handled.

Newest papers

Central Limit Theorems for Asynchronous Averaged Q-Learning 2026

Enhancing Inverse Reinforcement Learning through Encoding Dynamic Information in Reward Shaping 2026

Subgradient Method for System Identification with Non-Smooth Objectives 2026

Online Subspace Learning on Flag Manifolds for System Identification 2026

Learning Nonholonomic Dynamics with Constraint Discovery 2026

Constraint-Aware Reinforcement Learning via Adaptive Action Scaling 2026

Foundations of Safe Online Reinforcement Learning in the Linear Quadratic Regulator: √T-Regret 2026

Learning to accelerate distributed ADMM using graph neural networks 2026

Learning Multi-Robot Coordination with Invariant Consensus Stabilization 2026

Scalable Infinitesimal Generator–Based Koopman Learning for Long-Horizon Prediction 2026

Misinformation Mitigation over Social Networks: a Control Approach 2026

Can Optimal Transport Improve Federated Inverse Reinforcement Learning? 2026

Balance Equation-based Distributionally Robust Offline Imitation Learning 2026

Choose Wisely: Data-driven Predictive Control for Nonlinear Systems Using Online Data Selection 2026

Learning Dynamics from Input-Output Data with Hamiltonian Gaussian Processes 2026

Learning Quantized Continuous Controllers for Integer Hardware 2026

Adversarially Robust Multitask Adaptive Control 2026

Adaptive Policy Selection and Fine-Tuning under Interaction Budgets for Offline-to-Online Reinforcement Learning 2026

Koopman-BoxQP: Solving Large-Scale NMPC at kHz Rates 2026

Assumed Density Filtering and Smoothing with Neural Network Surrogate Models 2026

All L4DC 2026 papers →