35 citations · 67 across the 9 of their papers we have counts for
11 papers
Rebellion: Noise-Robust Reasoning Training for Audio Reasoning Models
Tiansheng Huang, Virat Shejwalkar, Oscar Chang +2
Instilling reasoning capabilities in large models (LMs) using reasoning training (RT) significantly improves LMs' performances. Thus Audio Reasoning Models (ARMs), i.e., audio LMs…
Assessing SATNet's Ability to Solve the Symbol Grounding Problem
Oscar Chang, Lampros Flokas, Hod Lipson +1
SATNet is an award-winning MAXSAT solver that can be used to infer logical rules and integrated as a differentiable layer in a deep neural network. It had been shown to solve Sudok…
Balanced and Deterministic Weight-sharing Helps Network Performance
Oscar Chang, Hod Lipson
Weight-sharing plays a significant role in the success of many deep neural networks, by increasing memory efficiency and incorporating useful inductive priors about the problem int…
Principled Weight Initialization for Hypernetworks
Oscar Chang, Lampros Flokas, Hod Lipson
Hypernetworks are meta neural networks that generate weights for a main neural network in an end-to-end differentiable manner. Despite extensive applications ranging from multi-tas…
Accelerating Meta-Learning by Sharing Gradients
Oscar Chang, Hod Lipson
The success of gradient-based meta-learning is primarily attributed to its ability to leverage related tasks to learn task-invariant information. However, the absence of interactio…
Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network
Oscar Chang, Yuling Yao, David Williams-King +1
Two main obstacles preventing the widespread adoption of variational Bayesian neural networks are the high parameter overhead that makes them infeasible on large networks, and the…
Seven Myths in Machine Learning Research
Oscar Chang, Hod Lipson
We present seven myths commonly believed to be true in machine learning research, circa Feb 2019. This is an archival copy of the blog post at https://crazyoscarchang.github.io/201…
PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences
Payel Das, Kahini Wadhawan, Oscar Chang +6
Given the emerging global threat of antimicrobial resistance, new methods for next-generation antimicrobial design are urgently needed. We report a peptide generation framework Pep…
Agent Embeddings: A Latent Representation for Pole-Balancing Networks
Oscar Chang, Robert Kwiatkowski, Siyuan Chen +1
We show that it is possible to reduce a high-dimensional object like a neural network agent into a low-dimensional vector representation with semantic meaning that we call agent em…
Neural Network Quine
Oscar Chang, Hod Lipson
Self-replication is a key aspect of biological life that has been largely overlooked in Artificial Intelligence systems. Here we describe how to build and train self-replicating ne…
Gradient Normalization & Depth Based Decay For Deep Learning
Robert Kwiatkowski, Oscar Chang
In this paper we introduce a novel method of gradient normalization and decay with respect to depth. Our method leverages the simple concept of normalizing all gradients in a deep…