D. Rus

发表

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery

Connor W. Coley, Alexander Amini, S. Bhatia, 2021, ACS central science.

TransCenter: Transformers with Dense Representations for Multiple-Object Tracking

Chuang Gan, Yutong Ban, Xavier Alameda-Pineda, 2021, 2103.15145.

On Coresets for Support Vector Machines

Murad Tukan, Dan Feldman, Cenk Baykal, 2020, TAMC.

Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition pdf

Alaa Maalouf, Dan Feldman, Lucas Liebenwein, 2021, NeurIPS.

BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

Huizi Mao, Zhijian Liu, Haotian Tang, 2022, ArXiv.

Toward understanding the communication in sperm whales

Daniel M. Vogt, S. Goldwasser, M. Bronstein, 2022, iScience.

Entangled Residual Mappings

Ramin M. Hasani, S. Hochreiter, T. Henzinger, 2022, ArXiv.

Identifying and Mitigating Potential Biases in Predicting Drug Approvals

A. Lo, Alexander Amini, D. Rus, 2022, Drug Safety.

Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks

S. Karaman, Wilko Schwarting, Igor Gilitschenski, 2022, L4DC.

GoTube: Scalable Statistical Verification of Continuous-Depth Models

Ramin M. Hasani, T. Henzinger, S. Smolka, 2022, AAAI.

Multi-Scale Feature Aggregation by Cross-Scale Pixel-to-Region Relation Operation for Semantic Segmentation

Marcelo H. Ang Jr, Yechao Bai, D. Rus, 2021, IEEE Robotics and Automation Letters.

A Deep Concept Graph Network for Interaction-Aware Trajectory Prediction

G. Rosman, S. Karaman, O. Meireles, 2022, 2022 International Conference on Robotics and Automation (ICRA).

The fMRI data center: An introduction

Michael S. Gazzaniga, Jeffrey S. Grethe, John D. Van Horn, 2001, NeuroImage.

Liquid Structural State-Space Models

Ramin M. Hasani, Alexander Amini, D. Rus, 2022, ICLR.

On the Forward Invariance of Neural ODEs

Ramin M. Hasani, D. Rus, Mathias Lechner, 2022, ICML.

TransCenter: Transformers With Dense Representations for Multiple-Object Tracking

Chuang Gan, Yutong Ban, Xavier Alameda-Pineda, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Solving Continuous Control via Q-learning

Martin A. Riedmiller, Markus Wulfmeier, Wilko Schwarting, 2022, ICLR.

Efficient Dataset Distillation Using Random Feature Approximation

Ramin M. Hasani, Alexander Amini, D. Rus, 2022, NeurIPS.

Interpreting Neural Policies with Disentangled Tree Representations

Ramin M. Hasani, T. Seyde, D. Rus, 2022, ArXiv.

Are All Vision Models Created Equal? A Study of the Open-Loop to Closed-Loop Causality Gap

Ramin M. Hasani, T. Henzinger, Alexander Amini, 2022, ArXiv.

Evolution of Neural Tangent Kernels under Benign and Adversarial Training

Ramin M. Hasani, Alexander Amini, D. Rus, 2022, NeurIPS.

Pruning by Active Attention Manipulation

Ramin M. Hasani, R. Grosu, Lucas Liebenwein, 2022, ArXiv.

Closed-form continuous-time neural networks

Ramin M. Hasani, G. Teschl, Alexander Amini, 2022, Nature Machine Intelligence.

Cooperative Flight Control Using Visual-Attention - Air-Guardian

Ramin M. Hasani, T. Seyde, Lianhao Yin, 2022, ArXiv.

Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing

Ramin M. Hasani, R. Grosu, D. Rus, 2021, 2022 International Conference on Robotics and Automation (ICRA).

Causal Navigation by Continuous-time Neural Networks pdf

Mathias Lechner, Ramin Hasani, Alexander Amini, 2021, NeurIPS.

Concept Graph Neural Networks for Surgical Video Understanding

Thomas M. Ward, G. Rosman, D. Hashimoto, 2022, ArXiv.

On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification

Radu Grosu, Mathias Lechner, Ramin Hasani, 2021, ICML.

Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning

T. Henzinger, Alexander Amini, D. Rus, 2022, IEEE Robotics and Automation Letters.

The Functional Magnetic Resonance Imaging Data Center (fMRIDC): the challenges and rewards of large-scale databasing of neuroimaging studies.

J B Woodward, J D Van Horn, J S Grethe, 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

Huizi Mao, Zhijian Liu, Haotian Tang, 2022, 2023 IEEE International Conference on Robotics and Automation (ICRA).

ActionSense: A Multimodal Dataset and Recording Framework for Human Activities Using Wearable Sensors in a Kitchen Environment

A. Torralba, W. Matusik, Yunzhu Li, 2022, NeurIPS.

Learning Interactive Driving Policies via Data-driven Simulation pdf

Igor Gilitschenski, Wilko Schwarting, Sertac Karaman, 2021, 2022 International Conference on Robotics and Automation (ICRA).

MapLite 2.0: Online HD Map Inference Using a Prior SD Map

Jeffrey M. Walls, Steven A. Parkison, Teddy Ort, 2022, IEEE Robotics and Automation Letters.

Concept Graph Neural Networks for Surgical Video Understanding

Thomas M. Ward, G. Rosman, D. Hashimoto, 2022, IEEE transactions on medical imaging.

Dataset Distillation with Convexified Implicit Gradients

Ramin M. Hasani, D. Rus, Mathias Lechner, 2023, ICML.

On the Size and Approximation Error of Distilled Sets

Ramin M. Hasani, D. Rus, Alaa Maalouf, 2023, ArXiv.

Dataset Distillation Fixes Dataset Reconstruction Attacks

Ramin M. Hasani, D. Rus, Mathias Lechner, 2023, ArXiv.

Differentiable Control Barrier Functions for Vision-based End-to-End Autonomous Driving

Ramin M. Hasani, Alexander Amini, D. Rus, 2022, ArXiv.

Closed-form continuous-time neural networks

Ramin M. Hasani, G. Teschl, Alexander Amini, 2021, Nature Machine Intelligence.

Provable Data Subset Selection For Efficient Neural Network Training

V. Braverman, Dan Feldman, D. Rus, 2023, arXiv.org.

BarrierNet: Differentiable Control Barrier Functions for Learning of Safe Robot Control

Ramin M. Hasani, Alexander Amini, D. Rus, 2023, IEEE Transactions on Robotics.

Robust flight navigation out of distribution with liquid neural networks

Ramin M. Hasani, Alexander Amini, D. Rus, 2023, Science Robotics.

Interpretable Autonomous Flight Via Compact Visualizable Neural Circuit Policies

Paul Tylkin, Alexander Amini, H. Siu, 2022, IEEE Robotics and Automation Letters.

Sparse Flows: Pruning Continuous-depth Models pdf

Ramin Hasani, Alexander Amini, Lucas Liebenwein, 2021, NeurIPS.

AutoCoreset: An Automatic Practical Coreset Construction Framework

V. Braverman, D. Rus, Alaa Maalouf, 2023, ICML.

Sensitivity-Informed Provable Pruning of Neural Networks

Dan Feldman, Cenk Baykal, Igor Gilitschenski, 2022, SIAM J. Math. Data Sci..

SafeDiffuser: Safe Planning with Diffusion Probabilistic Models

D. Rus, Chuang Gan, Tsun-Hsuan Wang, 2023, 2306.00148.

Learning Stability Attention in Vision-based End-to-end Driving Policies

Ramin M. Hasani, Alexander Amini, D. Rus, 2023, ArXiv.

Closed-form Continuous-Depth Models pdf

Mathias Lechner, Ramin Hasani, Max Tschaikowski, 2021, ArXiv.

Infrastructure-based End-to-End Learning and Prevention of Driver Failure

Ramin M. Hasani, S. Karaman, Yutong Ban, 2023, 2023 IEEE International Conference on Robotics and Automation (ICRA).

GROUNDED: A localizing ground penetrating radar evaluation dataset for learning to localize in inclement weather

Teddy Ort, Igor Gilitschenski, D. Rus, 2023, Int. J. Robotics Res..

PyHopper - Hyperparameter optimization

Ramin M. Hasani, D. Rus, Mathias Lechner, 2022, ArXiv.

Least-Mean-Squares Coresets for Infinite Streams

V. Braverman, Dan Feldman, D. Rus, 2023, IEEE Transactions on Knowledge and Data Engineering.

Follow Anything: Open-Set Detection, Tracking, and Following in Real-Time

Krishna Murthy Jatavallabhula, A. Torralba, D. Rus, 2023, IEEE Robotics and Automation Letters.

Deep Learning on Home Drone: Searching for the Optimal Architecture

Dan Feldman, D. Rus, O. Gal, 2022, 2023 IEEE International Conference on Robotics and Automation (ICRA).

Quantization-aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks

T. Henzinger, K. Chatterjee, D. Rus, 2022, AAAI Conference on Artificial Intelligence.

Capsa: A Unified Framework for Quantifying Risk in Deep Neural Networks

Alexander Amini, D. Rus, Elaheh Ahmadi, 2023, ArXiv.