Yali Amit

According to our database1, Yali Amit authored at least 38 papers between 1992 and 2021.

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Bibliography

2021
Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?
CoRR, 2021

EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss.
CoRR, 2021

2020
Exponential Tilting of Generative Models: Improving Sample Quality by Training and Sampling from Latent Energy.
CoRR, 2020

Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Deep Learning With Asymmetric Connections and Hebbian Updates.
Frontiers Comput. Neurosci., 2019

A Method to Model Conditional Distributions with Normalizing Flows.
CoRR, 2019

Generative Latent Flow: A Framework for Non-adversarial Image Generation.
CoRR, 2019

2018
Biologically plausible deep learning.
CoRR, 2018

2017
Detecting Curved Edges in Noisy Images in Sublinear Time.
J. Math. Imaging Vis., 2017

Deformable Classifiers.
CoRR, 2017

Dynamic Partition Models.
CoRR, 2017

2015
A Generative Statistical Algorithm for Automatic Detection of Complex Postures.
PLoS Comput. Biol., 2015

Sparse Autoregressive Networks.
CoRR, 2015

Compact Part-Based Image Representations: Extremal Competition and Overgeneralization.
Proceedings of the 3rd International Conference on Learning Representations, 2015

2014
Object Detection.
Computer Vision, A Reference Guide, 2014

Memory Capacity of Networks with Stochastic Binary Synapses.
PLoS Comput. Biol., 2014

2012
Recurrent network of perceptrons with three state synapses achieves competitive classification on real inputs.
Frontiers Comput. Neurosci., 2012

2011
Capacity analysis in multi-state synaptic models: a retrieval probability perspective.
J. Comput. Neurosci., 2011

2010
Precise Capacity Analysis in Binary Networks with Multiple Coding Level Inputs.
Neural Comput., 2010

2008
Efficient Annotation of Vesicle Dynamics Video Microscopy.
IEEE Trans. Pattern Anal. Mach. Intell., 2008

Optimizing One-Shot Learning with Binary Synapses.
Neural Comput., 2008

2007
POP: Patchwork of Parts Models for Object Recognition.
Int. J. Comput. Vis., 2007

2006
Generative Model and Consistent Estimation Algorithms for Non-Rigid Deformable Models.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Generative Models for Labeling Multi-object Configurations in Images.
Proceedings of the Toward Category-Level Object Recognition, 2006

2005
Part-Based Statistical Models for Object Classification and Detection.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

2004
A Coarse-to-Fine Strategy for Multiclass Shape Detection.
IEEE Trans. Pattern Anal. Mach. Intell., 2004

2001
Speech recognition using randomized relational decision trees.
IEEE Trans. Speech Audio Process., 2001

Attractor Networks for Shape Recognition.
Neural Comput., 2001

2000
A Neural Network Architecture for Visual Selection.
Neural Comput., 2000

1999
A Computational Model for Visual Selection.
Neural Comput., 1999

1997
Graphical Shape Templates for Automatic Anatomy Detection with Applications to MRI Brain Scans.
IEEE Trans. Medical Imaging, 1997

Joint Induction of Shape Features and Tree Classifiers.
IEEE Trans. Pattern Anal. Mach. Intell., 1997

Shape Quantization And Recognition With Randomized Trees.
Neural Comput., 1997

1996
Graphical Templates for Model Registration.
IEEE Trans. Pattern Anal. Mach. Intell., 1996

1994
A Nonlinear Variational Problem for Image Matching.
SIAM J. Sci. Comput., 1994

1993
Deformable template models for emission tomography.
IEEE Trans. Medical Imaging, 1993

Large deviations for coding Markov chains and Gibbs random fields.
IEEE Trans. Inf. Theory, 1993

1992
Large deviations for the asymptotics of Ziv-Lempel codes for 2-D Gibbs fields.
IEEE Trans. Inf. Theory, 1992


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