no code implementations • 3 May 2024 • Riley Simmons-Edler, Ryan Badman, Shayne Longpre, Kanaka Rajan
The recent embrace of machine learning (ML) in the development of autonomous weapons systems (AWS) creates serious risks to geopolitical stability and the free exchange of ideas in AI research.
no code implementations • 29 Sep 2021 • Muhammad Furqan Afzal, Christian D Marton, Erin L. Rich, Kanaka Rajan
Therefore, TRAKR can be used as a fast and accurate tool to distinguish patterns in complex nonlinear time-series data, such as neural recordings.
no code implementations • ICLR 2022 • Daniel R. Kepple, Rainer Engelken, Kanaka Rajan
Using recurrent neural networks (RNNs) and models of common experimental neuroscience tasks, we demonstrate that curricula can be used to differentiate learning principles using target-based and a representation-based loss functions as use cases.
no code implementations • 28 May 2021 • Christian David Márton, Léo Gagnon, Guillaume Lajoie, Kanaka Rajan
For this reason, a central aspect of human learning is the ability to recycle previously acquired knowledge in a way that allows for faster, less resource-intensive acquisition of new skills.
no code implementations • 15 May 2021 • Joseph D. Monaco, Kanaka Rajan, Grace M. Hwang
To motivate a brain basis of neural computation, we present a dynamical view of intelligence from which we elaborate concepts of sparsity in network structure, temporal dynamics, and interactive learning.
1 code implementation • 9 Oct 2017 • Brian DePasquale, Christopher J. Cueva, Kanaka Rajan, G. Sean Escola, L. F. Abbott
We present a target-based method for modifying the full connectivity matrix of a recurrent network to train it to perform tasks involving temporally complex input/output transformations.
no code implementations • NeurIPS 2010 • Kanaka Rajan, L Abbott, Haim Sompolinsky
How are the spatial patterns of spontaneous and evoked population responses related?