6 citations · 8 across the 9 of their papers we have counts for
9 papers
MulTTiPop: A Multitrack Transcription Dataset for Pop Music
Nathan Pruyne, Benjamin Stoler, William Chen +3
We present MulTTiPop, a dataset of pop music segments and their associated multitrack MIDI recordings for the evaluation of automatic music transcription models. MulTTiPop contains…
LongComp: Long-Tail Compositional Zero-Shot Generalization for Robust Trajectory Prediction
Benjamin Stoler, Jonathan Francis, Jean Oh
Methods for trajectory prediction in Autonomous Driving must contend with rare, safety-critical scenarios that make reliance on real-world data collection alone infeasible. To asse…
RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding
Benjamin Stoler, Juliet Yang, Jonathan Francis +1
Safety-critical scenarios are essential for training and evaluating autonomous driving (AD) systems, yet remain extremely rare in real-world driving datasets. To address this, we p…
SEAL: Towards Safe Autonomous Driving via Skill-Enabled Adversary Learning for Closed-Loop Scenario Generation
Benjamin Stoler, Ingrid Navarro, Jonathan Francis +1
Verification and validation of autonomous driving (AD) systems and components is of increasing importance, as such technology increases in real-world prevalence. Safety-critical sc…
SafeShift: Safety-Informed Distribution Shifts for Robust Trajectory Prediction in Autonomous Driving
Benjamin Stoler, Ingrid Navarro, Meghdeep Jana +3
As autonomous driving technology matures, safety and robustness of its key components, including trajectory prediction, is vital. Though real-world datasets, such as Waymo Open Mot…
Challenges in Close-Proximity Safe and Seamless Operation of Manned and Unmanned Aircraft in Shared Airspace
Jay Patrikar, Joao P. A. Dantas, Sourish Ghosh +11
We propose developing an integrated system to keep autonomous unmanned aircraft safely separated and behave as expected in conjunction with manned traffic. The main goal is to achi…
T2FPV: Dataset and Method for Correcting First-Person View Errors in Pedestrian Trajectory Prediction
Benjamin Stoler, Meghdeep Jana, Soonmin Hwang +1
Predicting pedestrian motion is essential for developing socially-aware robots that interact in a crowded environment. While the natural visual perspective for a social interaction…
Structural Similarity for Improved Transfer in Reinforcement Learning
C. Chace Ashcraft, Benjamin Stoler, Chigozie Ewulum +1
Transfer learning is an increasingly common approach for developing performant RL agents. However, it is not well understood how to define the relationship between the source and t…
Meta Arcade: A Configurable Environment Suite for Meta-Learning
Edward W. Staley, Chace Ashcraft, Benjamin Stoler +4
Most approaches to deep reinforcement learning (DRL) attempt to solve a single task at a time. As a result, most existing research benchmarks consist of individual games or suites…