activity
20182020
most citedLeveraging Medical Visual Question Answering with Supporting Facts

9 citations · 11 across the 3 of their papers we have counts for

collaborators

5 papers

cs.DC2020

Overview of the IBM Neural Computer Architecture

Pritish Narayanan, Charles E. Cox, Alexis Asseman +4

The IBM Neural Computer (INC) is a highly flexible, re-configurable parallel processing system that is intended as a research and development platform for emerging machine intellig…

cs.NE20191 cited

Simulation of neural function in an artificial Hebbian network

J. Campbell Scott, Thomas F. Hayes, Ahmet S. Ozcan +1

Artificial neural networks have diverged far from their early inspiration in neurology. In spite of their technological and commercial success, they have several shortcomings, most…

cs.CV20191 cited

Transfer Learning in Visual and Relational Reasoning

T. S. Jayram, Vincent Marois, Tomasz Kornuta +3

Transfer learning has become the de facto standard in computer vision and natural language processing, especially where labeled data is scarce. Accuracy can be significantly improv…

cs.CV20199 cited

Leveraging Medical Visual Question Answering with Supporting Facts

Tomasz Kornuta, Deepta Rajan, Chaitanya Shivade +2

In this working notes paper, we describe IBM Research AI (Almaden) team's participation in the ImageCLEF 2019 VQA-Med competition. The challenge consists of four question-answering…

cs.CV2018

On transfer learning using a MAC model variant

Vincent Marois, T. S. Jayram, Vincent Albouy +3

We introduce a variant of the MAC model (Hudson and Manning, ICLR 2018) with a simplified set of equations that achieves comparable accuracy, while training faster. We evaluate bot…