Barak A. Pearlmutter

Orcid: 0000-0003-0521-4553

According to our database1, Barak A. Pearlmutter authored at least 89 papers between 1986 and 2024.

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Bibliography

2024
Low-Rank Learning by Design: the Role of Network Architecture and Activation Linearity in Gradient Rank Collapse.
CoRR, 2024

2023
Comparing Differentiable Logics for Learning Systems: A Research Preview.
Proceedings of the Proceedings Fifth International Workshop on Formal Methods for Autonomous Systems, 2023

Visualization of AI Systems in Virtual Reality: A Comprehensive Review.
CoRR, 2023

Immersive Neural Network Exploration: A VR Approach to Human-Centered AI Understanding.
Proceedings of the 2023 Conference on Human Centered Artificial Intelligence: Education and Practice, 2023

Rich and Expressive Specification of Continuous-Learning Cyber-Physical Systems.
Proceedings of the 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2023

2022
Gradients without Backpropagation.
CoRR, 2022

2021
Continuous Convolutional Neural Networks: Coupled Neural PDE and ODE.
CoRR, 2021

Neural Network based on Automatic Differentiation Transformation of Numeric Iterate-to-Fixedpoint.
CoRR, 2021

ECG synthesis with Neural ODE and GAN models.
CoRR, 2021

HeunNet: Extending ResNet using Heun's Methods.
CoRR, 2021

Efficient Distributed Auto-Differentiation.
CoRR, 2021

2020
Neural ODEs for Informative Missingness in Multivariate Time Series.
CoRR, 2020

Neural Ordinary Differential Equation based Recurrent Neural Network Model.
CoRR, 2020

Lock-Free Hopscotch Hashing.
Proceedings of the 1st Symposium on Algorithmic Principles of Computer Systems, 2020

Automatic Differentiation of Sketched Regression.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Perturbation confusion in forward automatic differentiation of higher-order functions.
J. Funct. Program., 2019

Automatic Differentiation and Ubiquitous Adaptive Computing.
Proceedings of the Proceedings for the 27th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, 2019

2018
Divide-and-conquer checkpointing for arbitrary programs with no user annotation.
Optim. Methods Softw., 2018

Concurrent Robin Hood Hashing.
Proceedings of the 22nd International Conference on Principles of Distributed Systems, 2018

2017
Automatic Differentiation in Machine Learning: a Survey.
J. Mach. Learn. Res., 2017

Mini-symposium on automatic differentiation and its applications in the financial industry.
CoRR, 2017

2016
Editorial IEEE Transactions on Neural Networks and Learning Systems 2016 and Beyond.
IEEE Trans. Neural Networks Learn. Syst., 2016

Efficient Implementation of a Higher-Order Language with Built-In AD.
CoRR, 2016

Binomial Checkpointing for Arbitrary Programs with No User Annotation.
CoRR, 2016

Evolving the Incremental λ Calculus into a Model of Forward Automatic Differentiation (AD).
CoRR, 2016

Tricks from Deep Learning.
CoRR, 2016

DiffSharp: An AD Library for .NET Languages.
CoRR, 2016

2015
DiffSharp: Automatic Differentiation Library.
CoRR, 2015

Automatic differentiation in machine learning: a survey.
CoRR, 2015

2014
An Analysis of Publication Venues for Automatic Differentiation Research.
CoRR, 2014

Automatic Differentiation of Algorithms for Machine Learning.
CoRR, 2014

Seeing is Worse than Believing: Reading People's Minds Better than Computer-Vision Methods Recognize Actions.
Proceedings of the Computer Vision - ECCV 2014, 2014

2013
Block Coordinate Descent for Sparse NMF
Proceedings of the 1st International Conference on Learning Representations, 2013

2012
Confusion of Tagged Perturbations in Forward Automatic Differentiation of Higher-Order Functions
CoRR, 2012

AD in Fortran, Part 2: Implementation via Prepreprocessor
CoRR, 2012

AD in Fortran, Part 1: Design
CoRR, 2012

2011
Deep brain stimulation may reduce tremor by preferential blockade of slower axons via antidromic activation.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2009
A New Hypothesis for Sleep: Tuning for Criticality.
Neural Comput., 2009

Constructing Time-Frequency Dictionaries for Source Separation via Time-Frequency Masking and Source Localisation.
Proceedings of the Independent Component Analysis and Signal Separation, 2009

2008
Reverse-mode AD in a functional framework: Lambda the ultimate backpropagator.
ACM Trans. Program. Lang. Syst., 2008

Hemodynamics for Brain-Computer Interfaces.
IEEE Signal Process. Mag., 2008

Nesting forward-mode AD in a functional framework.
High. Order Symb. Comput., 2008

Discovering speech phones using convolutive non-negative matrix factorisation with a sparseness constraint.
Neurocomputing, 2008

The LOST Algorithm: Finding Lines and Separating Speech Mixtures.
EURASIP J. Adv. Signal Process., 2008

2007
Optimal Coding Predicts Attentional Modulation of Activity in Neural Systems.
Neural Comput., 2007

First-class nonstandard interpretations by opening closures.
Proceedings of the 34th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 2007

Lazy multivariate higher-order forward-mode AD.
Proceedings of the 34th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 2007

Discovering Convolutive Speech Phones Using Sparseness and Non-negativity.
Proceedings of the Independent Component Analysis and Signal Separation, 2007

Sparsification for Monaural Source Separation.
Proceedings of the Blind Speech Separation, 2007

2006
The VESPA: A method for the rapid estimation of a visual evoked potential.
NeuroImage, 2006

A Spectrum of Colors: Investigating the Temporal Frequency Characteristics of the Human Visual System Using a System Identification Approach.
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006

2005
Survey of sparse and non-sparse methods in source separation.
Int. J. Imaging Syst. Technol., 2005

Bounds on Query Convergence
CoRR, 2005

2004
A normative model of attention: receptive field modulation.
Neurocomputing, 2004

Monaural Source Separation Using Spectral Cues.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2004

Soft-LOST: EM on a Mixture of Oriented Lines.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2004

Transformations of Gaussian Process Priors.
Proceedings of the Deterministic and Statistical Methods in Machine Learning, 2004

2003
MEG source localization using an MLP with a distributed output representation.
IEEE Trans. Biomed. Eng., 2003

Single-trial detection in EEG and MEG: Keeping it linear.
Neurocomputing, 2003

Subject-Independent Magnetoencephalographic Source Localization by a Multilayer Perceptron.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Filtered Gaussian Processes for Learning with Large Data-Sets.
Proceedings of the Switching and Learning in Feedback Systems, 2003

2002
Independent Components of Magnetoencephalography: Single-Trial Response Onset Times.
NeuroImage, 2002

Linear Spatial Integration for Single-Trial Detection in Encephalography.
NeuroImage, 2002

Independent Components of Magnetoencephalography: Localization.
Neural Comput., 2002

2001
Blind Source Separation by Sparse Decomposition in a Signal Dictionary.
Neural Comput., 2001

Blind Source Separation via Multinode Sparse Representation.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

2000
Blind source separation of multichannel neuromagnetic responses.
Neurocomputing, 2000

Visualizing Communication between Neurons in the Lamina Ganglionaris of Musca domestica.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999
Detecting Intrusions using System Calls: Alternative Data Models.
Proceedings of the 1999 IEEE Symposium on Security and Privacy, 1999

An MEG Study of Response Latency and Variability in the Human Visual System During a Visual-Motor Integration Task.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Differentiating Functions of the Jacobian with Respect to the Weights.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998
Results of the Abbadingo One DFA Learning Competition and a New Evidence-Driven State Merging Algorithm.
Proceedings of the Grammatical Inference, 4th International Colloquium, 1998

1996
Doing the Twist: Diagonal Meshes Are Isomorphic to Twisted Toroidal Meshes.
IEEE Trans. Computers, 1996

VC Dimension of an Integrate-and-Fire Neuron Model.
Neural Comput., 1996

Garbage Collection with Pointers to Individual Cells.
Commun. ACM, 1996

Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1995
Gradient calculations for dynamic recurrent neural networks: a survey.
IEEE Trans. Neural Networks, 1995

Time-Skew Hebb rule in a nonisopotential neuron.
Neural Comput., 1995

1994
Fast Exact Multiplication by the Hessian.
Neural Comput., 1994

Simplifying Neural Network Soft Weight-sharing Measures by Soft Weight-measure Soft Weight Sharing.
Connect. Sci., 1994

Playing the Matching-Shoulders Lob-Pass Game with Logarithmic Regret.
Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, 1994

1992
Comments on 'Dynamic programming approach to optimal weight selection in multilayer neural networks' [with reply].
IEEE Trans. Neural Networks, 1992

Automatic Learning Rate Maximization in Large Adaptive Machines.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991
Gradient Descent: Second Order Momentum and Saturating Error.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

1990
Chaitin-Kolmogorov Complexity and Generalization in Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 3, 1990

1989
Learning State Space Trajectories in Recurrent Neural Networks.
Neural Comput., 1989

1988
Oaklisp: An Object-Oriented Dialect of Scheme.
LISP Symb. Comput., 1988

Using Backpropagation with Temporal Windows to Learn the Dynamics of the CMU Direct-Drive Arm II.
Proceedings of the Advances in Neural Information Processing Systems 1, 1988

1986
Oaklisp: an Object-Oriented Scheme with First Class Types.
Proceedings of the Conference on Object-Oriented Programming Systems, 1986


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