1 citations · 1 across the 4 of their papers we have counts for
4 papers
Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss
Vedant Shah, Aditya Agrawal, Lovekesh Vig +3
We are interested in neurosymbolic systems consisting of a high-level symbolic layer for explainable prediction in terms of human-intelligible concepts; and a low-level neural laye…
Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning
Dianbo Liu, Vedant Shah, Oussama Boussif +6
In cooperative multi-agent reinforcement learning, a team of agents works together to achieve a common goal. Different environments or tasks may require varying degrees of coordina…
Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel
Dianbo Liu, Vedant Shah, Oussama Boussif +6
In Multi-Agent Reinforcement Learning (MARL), specialized channels are often introduced that allow agents to communicate directly with one another. In this paper, we propose an alt…
Forecasting Market Prices using DL with Data Augmentation and Meta-learning: ARIMA still wins!
Vedant Shah, Gautam Shroff
Deep-learning techniques have been successfully used for time-series forecasting and have often shown superior performance on many standard benchmark datasets as compared to tradit…