← Authors

Daniela Rus

76 papers · 2008–2025 · 10 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (19) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (12) πŸƒ Academic Marathon (17) 🌈 Renaissance Researcher (9) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (10) 🀝 Dynamic Duo (20) πŸ‘‘ Triple Crown πŸ† Grand Slam 🧬 Topic Evolution πŸ† Keyword Champion πŸš€ Conference Pioneer πŸ”₯ Unstoppable (12) ⚑ Prolific Year (13) πŸ—ƒοΈ Keyword Collector (294) πŸ’Ž Century Club (76) ❓ The Questioner πŸ“ˆ Trend Setter

Conferences

NIPS (15) ICLR (13) ICML (13) RSS (12) CORL (9) L4DC (6) AAAI (5) ACL (1) CVPR (1) WACV (1)

Top co-authors

Ramin Hasani (20) Mathias Lechner (15) Alexander Amini (13) Wilko Schwarting (12) Igor Gilitschenski (11) Tim Seyde (11) Sertac Karaman (11) Tsun-Hsuan Wang (9) Radu Grosu (8) Dan Feldman (8)

Keywords

imitation learning (6) neural network (6) continuous control (4) model compression (3) sensor fusion (3) coreset construction (3) neural ordinary differential equation (3) approximation algorithm (3) dataset distillation (3) neural tangent kernel (3) receptive field (2) deep reinforcement learning (2) adversarial robustness (2) multi-agent reinforcement learning (2) generative model (2) upper confidence bound (2) motion planning (2) reinforcement learning (2) model-based reinforcement learning (2) uncertainty quantification (2)

Papers

ABNet: Adaptive explicit-Barrier Net for Safe and Scalable Robot Learning ICML 2025
Improving Efficiency of Sampling-based Motion Planning via Message-Passing Monte Carlo CORL 2025
Superfast Configuration-Space Convex Set Computation on GPUs for Online Motion Planning RSS 2025
SafeDiffuser: Safe Planning with Diffusion Probabilistic Models ICLR 2025
ReGen: Generative Robot Simulation via Inverse Design ICLR 2025
Oscillatory State-Space Models ICLR 2025
Visual Graph Arena: Evaluating Visual Conceptualization of Vision and Multimodal Large Language Models ICML 2025
TETRIS: Optimal Draft Token Selection for Batch Speculative Decoding ACL 2025
The Master Key Filters Hypothesis: Deep Filters Are General AAAI 2025
Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels ICLR 2024
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation ICLR 2024
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control ICLR 2024
DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning NIPS 2024
Growing Q-networks: Solving continuous control tasks with adaptive control resolution L4DC 2024
Gaussian Splatting to Real World Flight Navigation Transfer with Liquid Networks CORL 2024
Neural Echos: Depthwise Convolutional Filters Replicate Biological Receptive Fields WACV 2024
LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery ICML 2024
Large Scale Dataset Distillation with Domain Shift ICML 2024
Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning NIPS 2023
On the Forward Invariance of Neural ODEs ICML 2023
Measuring Interpretability of Neural Policies of Robots with Disentangled Representation CORL 2023
Dynamic Multi-Team Racing: Competitive Driving on 1/10-th Scale Vehicles via Learning in Simulation CORL 2023
Provable Data Subset Selection For Efficient Neural Networks Training ICML 2023
SoftZoo: A Soft Robot Co-design Benchmark For Locomotion In Diverse Environments ICLR 2023
DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models NIPS 2023
On the Size and Approximation Error of Distilled Datasets NIPS 2023
Liquid Structural State-Space Models ICLR 2023
Learning Stability Attention in Vision-based End-to-end Driving Policies L4DC 2023
Solving Continuous Control via Q-learning ICLR 2023
Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks AAAI 2023
Dataset Distillation with Convexified Implicit Gradients ICML 2023
AutoCoreset: An Automatic Practical Coreset Construction Framework ICML 2023
Evolution of Neural Tangent Kernels under Benign and Adversarial Training NIPS 2022
Efficient Dataset Distillation using Random Feature Approximation NIPS 2022
ActionSense: A Multimodal Dataset and Recording Framework for Human Activities Using Wearable Sensors in a Kitchen Environment NIPS 2022
Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models L4DC 2022
GoTube: Scalable Statistical Verification of Continuous-Depth Models AAAI 2022
Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks L4DC 2022
Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles CORL 2021
Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition NIPS 2021
Causal Navigation by Continuous-time Neural Networks NIPS 2021
Sparse Flows: Pruning Continuous-depth Models NIPS 2021
Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies NIPS 2021
Strength Through Diversity: Robust Behavior Learning via Mixture Policies CORL 2021
Learning A Risk-Aware Trajectory Planner From Demonstrations Using Logic Monitor CORL 2021
Liquid Time-constant Networks AAAI 2021
Deep Learning meets Projective Clustering ICLR 2021
The Logical Options Framework ICML 2021
On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification ICML 2021
Feedback from Pixels: Output Regulation via Learning-based Scene View Synthesis L4DC 2021
GROUNDED: The Localizing Ground Penetrating Radar Evaluation Dataset RSS 2021
Deep Evidential Regression NIPS 2020
Provable Filter Pruning for Efficient Neural Networks ICLR 2020
Deep Orientation Uncertainty Learning based on a Bingham Loss ICLR 2020
Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control ICML 2020
Differentiable Logic Layer for Rule Guided Trajectory Prediction CORL 2020
Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space CORL 2020
A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits ICML 2020
Deep Bayesian Nonparametric Learning of Rules and Plans from Demonstrations with a Learned Automaton Prior AAAI 2020
Learning to Plan via Deep Optimistic Value Exploration L4DC 2020
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds ICLR 2019
Learning to Plan with Logical Automata RSS 2019
Learning-In-The-Loop Optimization: End-To-End Control And Co-Design Of Soft Robots Through Learned Deep Latent Representations NIPS 2019
Plug-and-Play Supervisory Control Using Muscle and Brain Signals for Real-Time Gesture and Error Detection RSS 2018
Sampling-Based Approximation Algorithms for Reachability Analysis with Provable Guarantees RSS 2018
Coresets for Vector Summarization with Applications to Network Graphs ICML 2017
Information-Driven Adaptive Structured-Light Scanners CVPR 2016
Dimensionality Reduction of Massive Sparse Datasets Using Coresets NIPS 2016
Guaranteeing Spoof-Resilient Multi-Robot Networks RSS 2015
Coresets for k-Segmentation of Streaming Data NIPS 2014
Asking for Help Using Inverse Semantics RSS 2014
Distributed Approximation of Joint Measurement Distributions Using Mixtures of Gaussians RSS 2012
Practical Route Planning Under Delay Uncertainty: Stochastic Shortest Path Queries RSS 2012
What's in the Bag: A Distributed Approach to 3D Shape Duplication with Modular Robots RSS 2012
Load Balancing for Mobility-on-Demand Systems RSS 2011
Probabilistic Models of Object Geometry for Grasp Planning RSS 2008