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1908.07896
Cited By

Enabling hyperparameter optimization in sequential autoencoders for
spiking neural data

v1v2 (latest)

Enabling hyperparameter optimization in sequential autoencoders for spiking neural data

Neural Information Processing Systems (NeurIPS), 2019

21 August 2019

Mohammad Reza Keshtkaran

ArXiv (abs)PDF HTML

Papers citing "Enabling hyperparameter optimization in sequential autoencoders for spiking neural data"

14 / 14 papers shown

Brain-to-Text Benchmark '24: Lessons Learned

Brain-to-Text Benchmark '24: Lessons Learned

Francis R. Willett

...

E. Kelly Buchanan

Scott W. Linderman

Jaimie M. Henderson

245

8

0

23 Dec 2024

Diffusion-Based Generation of Neural Activity from Disentangled Latent
Codes

Diffusion-Based Generation of Neural Activity from Disentangled Latent Codes

Jonathan D. McCart

Andrew R. Sedler

Christopher Versteeg

Domenick M. Mifsud

Mattia Rigotti-Thompson

234

2

0

30 Jul 2024

Towards a "universal translator" for neural dynamics at single-cell,
single-spike resolution

Towards a "universal translator" for neural dynamics at single-cell, single-spike resolution

Donato Jimenez-Beneto

...

The International Brain Laboratory

313

38

0

19 Jul 2024

Latent Diffusion for Neural Spiking Data

Latent Diffusion for Neural Spiking Data

Jakob H. Macke

190

15

0

27 Jun 2024

Embedding-Aligned Language Models

Embedding-Aligned Language Models

Guy Tennenholtz

Craig Boutilier

387

5

0

24 May 2024

Predictive variational autoencoder for learning robust representations
of time-series data

Predictive variational autoencoder for learning robust representations of time-series data

Julia Huiming Wang

273

4

0

12 Dec 2023

lfads-torch: A modular and extensible implementation of latent factor
analysis via dynamical systems

lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systems

Andrew R. Sedler

216

12

0

03 Sep 2023

Decomposed Linear Dynamical Systems (dLDS) for learning the latent
components of neural dynamics

Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamicsJournal of machine learning research (JMLR), 2022

Christopher Rozell

Adam S. Charles

302

27

0

07 Jun 2022

A survey on multi-objective hyperparameter optimization algorithms for
Machine Learning

A survey on multi-objective hyperparameter optimization algorithms for Machine Learning

I. Nieuwenhuyse

Sebastian Rojas Gonzalez

296

155

0

23 Nov 2021

Deep inference of latent dynamics with spatio-temporal super-resolution
using selective backpropagation through time

Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through timeNeural Information Processing Systems (NeurIPS), 2021

Andrew R. Sedler

Harrison A. Grier

Mark A. Davenport

Matthew T. Kaufman

Andrea Giovannucci

255

11

0

29 Oct 2021

Neural Latents Benchmark '21: Evaluating latent variable models of
neural population activity

Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity

Raeed H. Chowdhury

...

Jonathan W. Pillow

Il Memming Park

591

118

0

09 Sep 2021

Representation learning for neural population activity with Neural Data
Transformers

Representation learning for neural population activity with Neural Data Transformers

443

80

0

02 Aug 2021

Learning identifiable and interpretable latent models of
high-dimensional neural activity using pi-VAE

Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE

457

102

0

09 Nov 2020

An Asymptotically Optimal Multi-Armed Bandit Algorithm and
Hyperparameter Optimization

An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter Optimization

275

8

0

11 Jul 2020

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