7 citations · 18 across the 5 of their papers we have counts for
5 papers
Scaling Up Computer Vision Neural Networks Using Fast Fourier Transform
Siddharth Agrawal
Deep Learning-based Computer Vision field has recently been trying to explore larger kernels for convolution to effectively scale up Convolutional Neural Networks. Simultaneously,…
Emergent Discrete Communication in Semantic Spaces
Mycal Tucker, Huao Li, Siddharth Agrawal +4
Neural agents trained in reinforcement learning settings can learn to communicate among themselves via discrete tokens, accomplishing as a team what agents would be unable to do al…
Adaptive Agent Architecture for Real-time Human-Agent Teaming
Tianwei Ni, Huao Li, Siddharth Agrawal +6
Teamwork is a set of interrelated reasoning, actions and behaviors of team members that facilitate common objectives. Teamwork theory and experiments have resulted in a set of stat…
Addressing reward bias in Adversarial Imitation Learning with neutral reward functions
Rohit Jena, Siddharth Agrawal, Katia Sycara
Generative Adversarial Imitation Learning suffers from the fundamental problem of reward bias stemming from the choice of reward functions used in the algorithm. Different types of…
Deep Variational Inference Without Pixel-Wise Reconstruction
Siddharth Agrawal, Ambedkar Dukkipati
Variational autoencoders (VAEs), that are built upon deep neural networks have emerged as popular generative models in computer vision. Most of the work towards improving variation…