Search Results for author:
Found 12 papers, 8 papers with code
JetMoE: Reaching Llama2 Performance with 0.1M Dollars
Large Language Models (LLMs) have achieved remarkable results, but their increasing resource demand has become a major obstacle to the development of powerful and accessible super-human intelligence.
OpenVoice: Versatile Instant Voice Cloning
The voice styles are not directly copied from and constrained by the style of the reference speaker.
SABLAS: Learning Safe Control for Black-box Dynamical Systems
Control certificates based on barrier functions have been a powerful tool to generate probably safe control policies for dynamical systems.
Reactive and Safe Road User Simulations using Neural Barrier Certificates
Reactive and safe agent modelings are important for nowadays traffic simulator designs and safe planning applications.
Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions
Safety and stability are common requirements for robotic control systems; however, designing safe, stable controllers remains difficult for nonlinear and uncertain models.
Density Constrained Reinforcement Learning
We study constrained reinforcement learning (CRL) from a novel perspective by setting constraints directly on state density functions, rather than the value functions considered by previous works.
MonoGRNet: A General Framework for Monocular 3D Object Detection
Detecting and localizing objects in the real 3D space, which plays a crucial role in scene understanding, is particularly challenging given only a monocular image due to the geometric information loss during imagery projection.
Learning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates
We propose a novel joint-learning framework that can be implemented in a decentralized fashion, with generalization guarantees for certain function classes.
Weakly Supervised 3D Object Detection from Point Clouds
A crucial task in scene understanding is 3D object detection, which aims to detect and localize the 3D bounding boxes of objects belonging to specific classes.
KETO: Learning Keypoint Representations for Tool Manipulation
For this purpose, we present KETO, a framework of learning keypoint representations of tool-based manipulation.
Robotics
Triangulation Learning Network: from Monocular to Stereo 3D Object Detection
In this paper, we study the problem of 3D object detection from stereo images, in which the key challenge is how to effectively utilize stereo information.
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization
We propose MonoGRNet for the amodal 3D object detection from a monocular RGB image via geometric reasoning in both the observed 2D projection and the unobserved depth dimension.
Ranked #26 on
Monocular 3D Object Detection
on KITTI Cars Moderate
