33 citations · 71 across the 8 of their papers we have counts for
8 papers
Desiderata for normative models of synaptic plasticity
Colin Bredenberg, Cristina Savin
Normative models of synaptic plasticity use a combination of mathematics and computational simulations to arrive at predictions of behavioral and network-level adaptive phenomena.…
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution
Anthony Zador, Sean Escola, Blake Richards +24
Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in…
A probabilistic framework for task-aligned intra- and inter-area neural manifold estimation
Edoardo Balzani, Jean Paul Noel, Pedro Herrero-Vidal +2
Latent manifolds provide a compact characterization of neural population activity and of shared co-variability across brain areas. Nonetheless, existing statistical tools for extra…
Current State and Future Directions for Learning in Biological Recurrent Neural Networks: A Perspective Piece
Luke Y. Prince, Roy Henha Eyono, Ellen Boven +9
We provide a brief review of the common assumptions about biological learning with findings from experimental neuroscience and contrast them with the efficiency of gradient-based l…
Online hyperparameter optimization by real-time recurrent learning
Daniel Jiwoong Im, Cristina Savin, Kyunghyun Cho
Conventional hyperparameter optimization methods are computationally intensive and hard to generalize to scenarios that require dynamically adapting hyperparameters, such as life-l…
A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks
Owen Marschall, Kyunghyun Cho, Cristina Savin
We present a framework for compactly summarizing many recent results in efficient and/or biologically plausible online training of recurrent neural networks (RNN). The framework or…
Using local plasticity rules to train recurrent neural networks
Owen Marschall, Kyunghyun Cho, Cristina Savin
To learn useful dynamics on long time scales, neurons must use plasticity rules that account for long-term, circuit-wide effects of synaptic changes. In other words, neural circuit…
How (not) to assess the importance of correlations for the matching of spontaneous and evoked activity
József Fiser, Máté Lengyel, Cristina Savin +2
A comment on `Population rate dynamics and multineuron firing patterns in sensory cortex' by Okun et al. Journal of Neuroscience 32(48):17108-17119, 2012 and our response to the co…