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Yali Amit
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2020 – today
- 2022
- [j24]Mufeng Tang, Yibo Yang, Yali Amit:
Biologically Plausible Training Mechanisms for Self-Supervised Learning in Deep Networks. Frontiers Comput. Neurosci. 16 (2022) - [i12]Angzhi Fan, Benjamin Ticknor, Yali Amit:
Detection Selection Algorithm: A Likelihood based Optimization Method to Perform Post Processing for Object Detection. CoRR abs/2212.05706 (2022) - 2021
- [i11]Zhisheng Xiao, Qing Yan, Yali Amit:
EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss. CoRR abs/2102.11757 (2021) - [i10]Zhisheng Xiao, Qing Yan, Yali Amit:
Do We Really Need to Learn Representations from In-domain Data for Outlier Detection? CoRR abs/2105.09270 (2021) - [i9]Mufeng Tang, Yibo Yang, Yali Amit:
Biologically Plausible Training Mechanisms for Self-Supervised Learning in Deep Networks. CoRR abs/2109.15089 (2021) - 2020
- [c5]Zhisheng Xiao, Qing Yan, Yali Amit:
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder. NeurIPS 2020 - [i8]Zhisheng Xiao, Qing Yan, Yali Amit:
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder. CoRR abs/2003.02977 (2020) - [i7]Zhisheng Xiao, Qing Yan, Yali Amit:
Exponential Tilting of Generative Models: Improving Sample Quality by Training and Sampling from Latent Energy. CoRR abs/2006.08100 (2020)
2010 – 2019
- 2019
- [j23]Yali Amit:
Deep Learning With Asymmetric Connections and Hebbian Updates. Frontiers Comput. Neurosci. 13: 18 (2019) - [i6]Zhisheng Xiao, Qing Yan, Yi-an Chen, Yali Amit:
Generative Latent Flow: A Framework for Non-adversarial Image Generation. CoRR abs/1905.10485 (2019) - [i5]Zhisheng Xiao, Qing Yan, Yali Amit:
A Method to Model Conditional Distributions with Normalizing Flows. CoRR abs/1911.02052 (2019) - 2018
- [i4]Yali Amit:
Biologically plausible deep learning. CoRR abs/1812.07965 (2018) - 2017
- [j22]Yi-Qing Wang, Alain Trouvé, Yali Amit, Boaz Nadler
:
Detecting Curved Edges in Noisy Images in Sublinear Time. J. Math. Imaging Vis. 59(3): 373-393 (2017) - [i3]Marc Goessling, Yali Amit:
Dynamic Partition Models. CoRR abs/1702.04832 (2017) - [i2]Jiajun Shen, Yali Amit:
Deformable Classifiers. CoRR abs/1712.06715 (2017) - 2015
- [j21]Stanislav Nagy, Marc Goessling, Yali Amit, David Biron:
A Generative Statistical Algorithm for Automatic Detection of Complex Postures. PLoS Comput. Biol. 11(10) (2015) - [c4]Marc Goessling, Yali Amit:
Compact Part-Based Image Representations: Extremal Competition and Overgeneralization. ICLR (Workshop) 2015 - [i1]Marc Goessling, Yali Amit:
Sparse Autoregressive Networks. CoRR abs/1511.04776 (2015) - 2014
- [j20]Alexis M. Dubreuil, Yali Amit, Nicolas Brunel:
Memory Capacity of Networks with Stochastic Binary Synapses. PLoS Comput. Biol. 10(8) (2014) - [r1]Yali Amit, Pedro F. Felzenszwalb:
Object Detection. Computer Vision, A Reference Guide 2014: 537-542 - 2012
- [j19]Yali Amit, Jacob Walker:
Recurrent network of perceptrons with three state synapses achieves competitive classification on real inputs. Frontiers Comput. Neurosci. 6: 39 (2012) - 2011
- [j18]Yibi Huang, Yali Amit:
Capacity analysis in multi-state synaptic models: a retrieval probability perspective. J. Comput. Neurosci. 30(3): 699-720 (2011) - 2010
- [j17]Yali Amit, Yibi Huang:
Precise Capacity Analysis in Binary Networks with Multiple Coding Level Inputs. Neural Comput. 22(3): 660-688 (2010)
2000 – 2009
- 2008
- [j16]Sandro Romani
Optimizing One-Shot Learning with Binary Synapses. Neural Comput. 20(8): 1928-1950 (2008) - [j15]Leandro Cortes, Yali Amit:
Efficient Annotation of Vesicle Dynamics Video Microscopy. IEEE Trans. Pattern Anal. Mach. Intell. 30(11): 1998-2010 (2008) - 2007
- [j14]Yali Amit, Alain Trouvé:
POP: Patchwork of Parts Models for Object Recognition. Int. J. Comput. Vis. 75(2): 267-282 (2007) - 2006
- [c3]Yali Amit, Alain Trouvé:
Generative Models for Labeling Multi-object Configurations in Images. Toward Category-Level Object Recognition 2006: 362-381 - [c2]Stéphanie Allassonnière, Estelle Kuhn, Alain Trouvé, Yali Amit:
Generative Model and Consistent Estimation Algorithms for Non-Rigid Deformable Models. ICASSP (5) 2006: 929-932 - 2005
- [c1]Elliot Joel Bernstein, Yali Amit:
Part-Based Statistical Models for Object Classification and Detection. CVPR (2) 2005: 734-740 - 2004
- [j13]Yali Amit, Donald Geman, Xiaodong Fan:
A Coarse-to-Fine Strategy for Multiclass Shape Detection. IEEE Trans. Pattern Anal. Mach. Intell. 26(12): 1606-1621 (2004) - 2001
- [j12]Yali Amit, Massimo Mascaro:
Attractor Networks for Shape Recognition. Neural Comput. 13(6): 1415-1442 (2001) - [j11]Yali Amit, Alejandro Murua:
Speech recognition using randomized relational decision trees. IEEE Trans. Speech Audio Process. 9(4): 333-341 (2001) - 2000
- [j10]Yali Amit:
A Neural Network Architecture for Visual Selection. Neural Comput. 12(5): 1141-1164 (2000)
1990 – 1999
- 1999
- [j9]Yali Amit, Donald Geman:
A Computational Model for Visual Selection. Neural Comput. 11(7): 1691-1715 (1999) - 1997
- [j8]Yali Amit, Donald Geman:
Shape Quantization And Recognition With Randomized Trees. Neural Comput. 9(7): 1545-1588 (1997) - [j7]Yali Amit, Kenneth Wilder:
Joint Induction of Shape Features and Tree Classifiers. IEEE Trans. Pattern Anal. Mach. Intell. 19(11): 1300-1305 (1997) - [j6]Yali Amit:
Graphical Shape Templates for Automatic Anatomy Detection with Applications to MRI Brain Scans. IEEE Trans. Medical Imaging 16(1): 28-40 (1997) - 1996
- [j5]Yali Amit, Augustine Kong
Graphical Templates for Model Registration. IEEE Trans. Pattern Anal. Mach. Intell. 18(3): 225-236 (1996) - 1994
- [j4]Yali Amit:
A Nonlinear Variational Problem for Image Matching. SIAM J. Sci. Comput. 15(1): 207-224 (1994) - 1993
- [j3]Yali Amit, Michael I. Miller:
Large deviations for coding Markov chains and Gibbs random fields. IEEE Trans. Inf. Theory 39(1): 109-118 (1993) - [j2]Yali Amit, Kevin M. Manbeck:
Deformable template models for emission tomography. IEEE Trans. Medical Imaging 12(2): 260-268 (1993) - 1992
- [j1]Yali Amit, Michael I. Miller:
Large deviations for the asymptotics of Ziv-Lempel codes for 2-D Gibbs fields. IEEE Trans. Inf. Theory 38(4): 1271-1275 (1992)
Coauthor Index
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