2 citations · 6 across the 7 of their papers we have counts for
7 papers
Iterative Refinement Neural Operators are Learned Fixed-Point Solvers: A Principled Approach to Spectral Bias Mitigation
Xiaotian Liu, Shuyuan Shang, Xiaopeng Wang +2
Neural operators serve as fast, data-driven surrogates for scientific modeling but typically rely on a monolithic, single-pass inference procedure that struggles to resolve high-fr…
RL4RLA: Teaching ML to Discover Randomized Linear Algebra Algorithms Through Curriculum Design and Graph-Based Search
Jinglong Xiong, Xiaotian Liu, Ruoxin Wang +4
Randomized linear algebra (RLA) algorithms are a modern class of numerical linear algebra techniques that play an essential role in scientific computing and machine learning, with…
Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance
Haiquan Lu, Xiaotian Liu, Yefan Zhou +6
Recent studies on deep ensembles have identified the sharpness of the local minima of individual learners and the diversity of the ensemble members as key factors in improving test…
Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode
Jinyang Jiang, Xiaotian Liu, Tao Ren +5
We introduce a deep reinforcement learning (DRL) approach for solving management problems including inventory management, dynamic pricing, and recommendation. This DRL approach has…
Improving Generalization in Task-oriented Dialogues with Workflows and Action Plans
Stefania Raimondo, Christopher Pal, Xiaotian Liu +2
Task-oriented dialogue is difficult in part because it involves understanding user intent, collecting information from the user, executing API calls, and generating helpful and flu…
Egocentric Planning for Scalable Embodied Task Achievement
Xiaotian Liu, Hector Palacios, Christian Muise
Embodied agents face significant challenges when tasked with performing actions in diverse environments, particularly in generalizing across object types and executing suitable act…
pyRDDLGym: From RDDL to Gym Environments
Ayal Taitler, Michael Gimelfarb, Jihwan Jeong +4
We present pyRDDLGym, a Python framework for auto-generation of OpenAI Gym environments from RDDL declerative description. The discrete time step evolution of variables in RDDL is…