Mathias Lechner
23 papers · 2020–2025 · 4 venues · across top CS/AI venues
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🗺️ Taxonomy Completionist (45) 🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Topic Evolution
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Dynamic Duo
(16)
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(6)
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Machine Learning
(16)
Artificial Intelligence
(14)
Deep Learning
(14)
Core AI
(14)
Optimization & Theory · Machine Learning
(12)
Architectures
(8)
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(7)
Reinforcement Learning
(5)
Optimization & Theory · Deep Learning
(5)
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Mathematics & Optimization
(2)
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(2)
Keywords
formal verification
(6)
neural network
(4)
reinforcement learning
(4)
dataset distillation
(4)
neural ordinary differential equation
(3)
stochastic control
(3)
reach-avoid specification
(2)
reachability analysis
(2)
continuous-time neural network
(2)
neural network verification
(2)
quantized neural network
(2)
recurrent neural network
(2)
model compression
(2)
neural tangent kernel
(2)
state space model
(2)
control barrier function
(2)
convex optimization
(1)
binary classification
(1)
multi-agent reinforcement learning
(1)
imitation learning
(1)
Papers
SafeDiffuser: Safe Planning with Diffusion Probabilistic Models
ICLR 2025
Large Scale Dataset Distillation with Domain Shift
ICML 2024
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control
ICLR 2024
State-Free Inference of State-Space Models: The *Transfer Function* Approach
ICML 2024
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation
ICLR 2024
Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees
NeurIPS 2023
Dataset Distillation with Convexified Implicit Gradients
ICML 2023
Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning
NeurIPS 2023
Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees
AAAI 2023
Liquid Structural State-Space Models
ICLR 2023
On the Forward Invariance of Neural ODEs
ICML 2023
On the Size and Approximation Error of Distilled Datasets
NeurIPS 2023
Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks
AAAI 2023
GoTube: Scalable Statistical Verification of Continuous-Depth Models
AAAI 2022
Stability Verification in Stochastic Control Systems via Neural Network Supermartingales
AAAI 2022
Causal Navigation by Continuous-time Neural Networks
NeurIPS 2021
Infinite Time Horizon Safety of Bayesian Neural Networks
NeurIPS 2021
Liquid Time-constant Networks
AAAI 2021
On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification
ICML 2021
On the Verification of Neural ODEs with Stochastic Guarantees
AAAI 2021
Scalable Verification of Quantized Neural Networks
AAAI 2021
A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits
ICML 2020
Learning representations for binary-classification without backpropagation
ICLR 2020