Ramin Hasani
23 papers · 2019–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (6) π Academic Marathon (6) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (7)
π
Cross-Pollinator
(7)
π
Renaissance Researcher
(6)
πΊοΈ
Taxonomy Completionist
(45)
π€
Dynamic Duo
(20)
π
Keyword Champion
(4)
π
Triple Crown
π
Grand Slam
π
Century Club
(23)
π
Conference Pioneer
β‘
Prolific Year
(5)
ποΈ
Keyword Collector
(90)
π₯
Unstoppable
(7)
Conferences
ICML (6)
NIPS (6)
AAAI (4)
ICLR (4)
CORL (2)
L4DC (1)
Top co-authors
Keywords
neural ordinary differential equation
(4)
neural tangent kernel
(3)
dataset distillation
(3)
model compression
(2)
continuous-time neural network
(2)
kernel ridge regression
(2)
neural network
(2)
reachability analysis
(2)
formal verification
(2)
reinforcement learning
(1)
knowledge distillation
(1)
convex optimization
(1)
adversarial training
(1)
random feature approximation
(1)
causal inference
(1)
anomaly detection
(1)
global optimization
(1)
imitation learning
(1)
image classification
(1)
robot learning
(1)
Papers
SafeDiffuser: Safe Planning with Diffusion Probabilistic Models
ICLR 2025
Gaussian Splatting to Real World Flight Navigation Transfer with Liquid Networks
CORL 2024
State-Free Inference of State-Space Models: The *Transfer Function* Approach
ICML 2024
Large Scale Dataset Distillation with Domain Shift
ICML 2024
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control
ICLR 2024
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation
ICLR 2024
Dataset Distillation with Convexified Implicit Gradients
ICML 2023
Liquid Structural State-Space Models
ICLR 2023
Learning Stability Attention in Vision-based End-to-end Driving Policies
L4DC 2023
Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning
NIPS 2023
On the Size and Approximation Error of Distilled Datasets
NIPS 2023
Measuring Interpretability of Neural Policies of Robots with Disentangled Representation
CORL 2023
On the Forward Invariance of Neural ODEs
ICML 2023
GoTube: Scalable Statistical Verification of Continuous-Depth Models
AAAI 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training
NIPS 2022
Efficient Dataset Distillation using Random Feature Approximation
NIPS 2022
On the Verification of Neural ODEs with Stochastic Guarantees
AAAI 2021
On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification
ICML 2021
Causal Navigation by Continuous-time Neural Networks
NIPS 2021
Liquid Time-constant Networks
AAAI 2021
Sparse Flows: Pruning Continuous-depth Models
NIPS 2021
A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits
ICML 2020
A Machine Learning Suite for Machine Componentsβ Health-Monitoring
AAAI 2019