Y. Amit

发表

Structural Image Restoration through Deformable Templates

U. Grenander, Y. Amit, M. Piccioni, 1991 .

A Computational Model for Visual Selection

Yali Amit, Donald Geman, D. Geman, 1999, Neural Computation.

Efficient Focusing and Face Detection

D. Geman, Y. Amit, B. Jedynak, 1998 .

Joint Induction of Shape Features and Tree Classifiers

Yali Amit, Kenneth Wilder, Y. Amit, 1997, IEEE Trans. Pattern Anal. Mach. Intell..

Randomized Inquiries About Shape: An Application to Handwritten Digit Recognition.

D. Geman, Y. Amit, 1994 .

An integrated network for invariant visual detection and recognition

Y. Amit, M. Mascaro, Massimo Mascaro, 2003, Vision Research.

Computational Strategies for Model-Based Scene Interpretation

D. Geman, Y. Amit, Xiaodong Fan, 2003 .

POP: Patchwork of Parts Models for Object Recognition

Yali Amit, Alain Trouvé, Y. Amit, 2007, International Journal of Computer Vision.

Statistical models for object classification and detection

Y. Amit, E. Bernstein, 2006 .

Towards a coherent statistical framework for dense deformable template estimation

Y. Amit, A. Trouvé, S. Allassonnière, 2007 .

Part-based statistical models for object classification and detection

Yali Amit, Elliot Joel Bernstein, Y. Amit, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

Shape Quantization and Recognition with Randomized Trees

Yali Amit, Donald Geman, D. Geman, 1997, Neural Computation.

Graphical Templates for Model Registration

Yali Amit, Augustine Kong, Y. Amit, 1996, IEEE Trans. Pattern Anal. Mach. Intell..

Sequential Learning of Reusable Parts for Object Detection

Yali Amit, Donald Geman, S. Krempp, 2003 .

A Nonhomogeneous Markov Process for the Estimation of Gaussian Random Fields with Nonlinear Observations

Y. Amit, M. Piccioni, 1991 .

A Neural Network Architecture for Visual Selection

Yali Amit, Y. Amit, 2000, Neural Computation.

Encoding of Movement Fragments in the Motor Cortex

Y. Amit, N. Hatsopoulos, Q. Xu, 2007, The Journal of Neuroscience.

Convergence properties of the Gibbs sampler for perturbations of Gaussians

Y. Amit, 1996 .

2D Object Detection and Recognition

Yali Amit, Y. Amit, 2002 .

A multiflow approximation to diffusions

Y. Amit, 1991 .

2D Object Detection and Recognition: Models, Algorithms, and Networks

Yali Amit, Y. Amit, 2002 .

A Nonlinear Variational Problem for Image Matching

Yali Amit, Y. Amit, 1994, SIAM J. Sci. Comput..

A coarse-to-fine strategy for multiclass shape detection

Yali Amit, Donald Geman, Xiaodong Fan, 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Synthesizing complex movement fragment representations from motor cortical ensembles

Y. Amit, N. Hatsopoulos, 2012, Journal of Physiology-Paris.

Inferring learning rules from distribution of firing rates in cortical neurons

David J. Freedman, David L. Sheinberg, D. Sheinberg, 2015, Nature Neuroscience.

Heterogeneous neural coding of corrective movements in motor cortex

Adam S Dickey, Y. Amit, N. Hatsopoulos, 2013, Front. Neural Circuits.

Encoding of Coordinated Grasp Trajectories in Primary Motor Cortex

Yali Amit, Kazutaka Takahashi, Nicholas G Hatsopoulos, 2010, The Journal of Neuroscience.

WAVELET SNAKE FOR CLASSIFICATION OF NODULES ANDFALSE POSITIVES IN DIGITAL CHEST

Y. Amit, RADIOGRAPHSHiroyuki Yoshiday, Shigehiko Katsuragawaz, 1997 .

Movements: A Cluster Analysis Cortex Hand Area During Individuated Finger Limited Functional Grouping of Neurons in the Motor

E. Bizzi, V. Cheung, Y. Amit, 2015 .

On rates of convergence of stochastic relaxation for Gaussian and non-Gaussian distributions

Y. Amit, 1991 .

Single-unit stability using chronically implanted multielectrode arrays.

Yali Amit, Nicholas G Hatsopoulos, Aaron Suminski, 2009, Journal of neurophysiology.

Deformable template models for emission tomography

Yali Amit, Kevin M. Manbeck, Y. Amit, 1993, IEEE Trans. Medical Imaging.

Large deviations for coding Markov chains and Gibbs random fields

Yali Amit, Michael I. Miller, Y. Amit, 1993, IEEE Trans. Inf. Theory.

Efficient Annotation of Vesicle Dynamics Video Microscopy

Yali Amit, Leandro Cortes, Y. Amit, 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Efficient Detection and Tracking of Multiple Vesicles in Video Microscopy

Yali Amit, Y. Amit, Leandro Cortés, 2007 .

It's hard to forget: resetting memory in delay-match-to-multiple-image tasks

Yali Amit, Shaul Hochstein, Volodya Yakovlev, 2013, Front. Hum. Neurosci..

Memory capacity of networks with stochastic binary synapses

Yali Amit, Nicolas Brunel, Alexis M. Dubreuil, 2013, BMC Neuroscience.

Memory Capacity of Networks with Stochastic Binary Synapses

Yali Amit, Nicolas Brunel, Alexis M. Dubreuil, 2013, PLoS Comput. Biol..

Optimizing One-Shot Learning with Binary Synapses

Yali Amit, Daniel J. Amit, Sandro Romani, 2008, Neural Computation.

EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss pdf

Yali Amit, Qing Yan, Zhisheng Xiao, 2021, ArXiv.

Dynamic Partition Models pdf

Yali Amit, Marc Goessling, Y. Amit, 2017, ArXiv.

Exponential Tilting of Generative Models: Improving Sample Quality by Training and Sampling from Latent Energy pdf

Yali Amit, Qing Yan, Zhisheng Xiao, 2020, ArXiv.

Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder pdf

Yali Amit, Qing Yan, Zhisheng Xiao, 2020, NeurIPS.

Compact Compositional Models

Yali Amit, Marc Goessling, Y. Amit, 2014 .

Compact Part-Based Image Representations

Yali Amit, Marc Goessling, Y. Amit, 2014, 1412.3708.

Blockage of eye-closure-generated generalized paroxysms by mental activity

D. Amit, Y. Amit, R. Amit, 2006, Journal of Pediatric Neurology.

Large deviations for the asymptotics of Ziv-Lempel codes for 2-D Gibbs fields

Michael I. Miller, Y. Amit, Y. Amit, 1992, IEEE Trans. Inf. Theory.

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

Y. Amit, Zhisheng Xiao, Qing Yan, 2021, ArXiv.

Deep Learning With Asymmetric Connections and Hebbian Updates

Yali Amit, Y. Amit, 2018, Front. Comput. Neurosci..

Object Detection

Yali Amit, Pedro F. Felzenszwalb, Y. Amit, 2020, Computer Vision, A Reference Guide.

2D Models: Deformable Images

Yali Amit, Y. Amit, 2002 .

Detecting Curved Edges in Noisy Images in Sublinear Time

Yali Amit, Alain Trouvé, Boaz Nadler, 2017, Journal of Mathematical Imaging and Vision.

Biologically Plausible Training Mechanisms for Self-Supervised Learning in Deep Networks

Y. Amit, Yibo Yang, Mufeng Tang, 2021, Frontiers in Computational Neuroscience.

Capacity analysis in multi-state synaptic models: a retrieval probability perspective

Yali Amit, Yibi Huang, Y. Amit, 2011, Journal of Computational Neuroscience.

Generative Latent Flow

Yali Amit, Zhisheng Xiao, Qing Yan, 2019 .

A Generative Statistical Algorithm for Automatic Detection of Complex Postures

Yali Amit, Marc Goessling, Stanislav Nagy, 2015, PLoS Comput. Biol..

Precise Capacity Analysis in Binary Networks with Multiple Coding Level Inputs

Yali Amit, Yibi Huang, Y. Amit, 2010, Neural Computation.

Standards of skinfold thickness and anthropometric indices in term Israeli newborn infants.

Y. Amit, I. Arad, Y. Amit, 1993, Israel journal of medical sciences.

Biologically plausible deep learning pdf

Yali Amit, Y. Amit, 2018, ArXiv.

Mathematical textbook of deformable neuroanatomies.

M I Miller, G E Christensen, Y Amit, 1993, Proceedings of the National Academy of Sciences of the United States of America.

Generative Latent Flow: A Framework for Non-adversarial Image Generation pdf

Yali Amit, Zhisheng Xiao, Qing Yan, 2019, ArXiv.

Ergodic properties of markov processes driven by a set of vector fields

Y. Amit, 1989 .

Detection Selection Algorithm: A Likelihood based Optimization Method to Perform Post Processing for Object Detection

Y. Amit, An Fan, Benjamin Ticknor, 2022, ArXiv.

Modeling behavior in different delay match to sample tasks in one simple network

Yali Amit, Shaul Hochstein, Volodya Yakovlev, 2013, Front. Hum. Neurosci..

Recurrent network of perceptrons with three state synapses achieves competitive classification on real inputs

Yali Amit, Jacob Walker, Y. Amit, 2012, Front. Comput. Neurosci..

Capacity analysis in multi-state synaptic models: a retrieval probability perspective

Y. Amit, Yibi Huang, 2011, Journal of Computational Neuroscience.

Hand Position and Velocity Spatiotemporal Tuning of Motor Cortical Neurons for Encoding of Coordinated Grasp Trajectories in Primary Motor Cortex Machine − Incorporating Feedback from Multiple Sensory Modalities Enhances Brain Anisotropic, Gain-encoding Primitives for Motor Adaptation Linear Hyperge

Dennis C. Tkach, Gary C. Sing, Wilsaan M. Joiner, 2004 .

Graphical shape templates for automatic anatomy detection with applications to MRI brain scans

Y. Amit, 1997, IEEE Transactions on Medical Imaging.

Global shape models for optical sectioning microscopy

U. Grenander, Y. Amit, M. Miller, 1992, Optical Society of America Annual Meeting.

Comparing sweep strategies for stochastic relaxation

U. Grenander, Y. Amit, 1991 .

Speech recognition using randomized relational decision trees

Yali Amit, Alejandro Murua, Y. Amit, 2001, IEEE Trans. Speech Audio Process..