Tomer Galanti

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 44

Top Topics

Image Generation

Semantic Mappings

Generalization Bounds

Top Venues

Trans. Mach. Learn. Res.

Publications

Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Oren Pereg, Moshe Wasserblat, Tomer Galanti, Michal Gordon, David Harel
Distributed Speculative Inference of Large Language Models. CoRR (2024)
Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun
Reverse Engineering Self-Supervised Learning. NeurIPS (2023)
Akshay Rangamani, Marius Lindegaard, Tomer Galanti, Tomaso A. Poggio
Feature learning in deep classifiers through Intermediate Neural Collapse. ICML (2023)
Ido Ben-Shaul, Tomer Galanti, Shai Dekel
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions. Trans. Mach. Learn. Res. 2023 (2023)
Ido Ben-Shaul, Tomer Galanti, Shai Dekel
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions. CoRR (2023)
Tomer Galanti, Liane Galanti, Ido Ben-Shaul
Comparative Generalization Bounds for Deep Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Tomer Galanti, Mengjia Xu, Liane Galanti, Tomaso A. Poggio
Norm-based Generalization Bounds for Compositionally Sparse Neural Networks. CoRR (2023)
Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun
Reverse Engineering Self-Supervised Learning. CoRR (2023)
Ameen Ali, Tomer Galanti, Lior Wolf
Centered Self-Attention Layers. CoRR (2023)
Tomer Galanti, Mengjia Xu, Liane Galanti, Tomaso A. Poggio
Norm-based Generalization Bounds for Sparse Neural Networks. NeurIPS (2023)
Ziyin Liu, Botao Li, Tomer Galanti, Masahito Ueda
The Probabilistic Stability of Stochastic Gradient Descent. CoRR (2023)
Tomer Galanti
A Note on the Implicit Bias Towards Minimal Depth of Deep Neural Networks. CoRR (2022)
Chenfeng Xu, Shijia Yang, Tomer Galanti, Bichen Wu, Xiangyu Yue, Bohan Zhai, Wei Zhan, Peter Vajda, Kurt Keutzer, Masayoshi Tomizuka
Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models. ECCV (37) (2022)
Tomer Galanti, András György, Marcus Hutter
On the Role of Neural Collapse in Transfer Learning. ICLR (2022)
Ameen Ali, Tomer Galanti, Evgenii Zheltonozhskii, Chaim Baskin, Lior Wolf
Weakly Supervised Discovery of Semantic Attributes. CLeaR (2022)
Tomer Galanti, András György, Marcus Hutter
Generalization Bounds for Transfer Learning with Pretrained Classifiers. CoRR (2022)
Tomer Galanti, Tomaso A. Poggio
SGD Noise and Implicit Low-Rank Bias in Deep Neural Networks. CoRR (2022)
Tomer Galanti, Sagie Benaim, Lior Wolf
Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs. J. Mach. Learn. Res. 22 (2021)
Etai Littwin, Tomer Galanti, Lior Wolf
On random kernels of residual architectures. UAI (2021)
Ameen Ali, Tomer Galanti, Evgeniy Zheltonozhskiy, Chaim Baskin, Lior Wolf
Intersection Regularization for Extracting Semantic Attributes. CoRR (2021)
Raphael Bensadoun, Shir Gur, Tomer Galanti, Lior Wolf
Meta Internal Learning. NeurIPS (2021)
Tomer Galanti, András György, Marcus Hutter
On the Role of Neural Collapse in Transfer Learning. CoRR (2021)
Raphael Bensadoun, Shir Gur, Tomer Galanti, Lior Wolf
Meta Internal Learning. CoRR (2021)
Yaniv Benny, Tomer Galanti, Sagie Benaim, Lior Wolf
Evaluation Metrics for Conditional Image Generation. Int. J. Comput. Vis. 129 (5) (2021)
Tomer Galanti, Ofir Nabati, Lior Wolf
A Critical View of the Structural Causal Model. CoRR (2020)
Tomer Galanti, Lior Wolf
On the Modularity of Hypernetworks. NeurIPS (2020)
Lior Wolf, Tomer Galanti, Tamir Hazan
A Formal Approach to Explainability. CoRR (2020)
Etai Littwin, Tomer Galanti, Lior Wolf, Greg Yang
On Infinite-Width Hypernetworks. NeurIPS (2020)
Ori Press, Tomer Galanti, Sagie Benaim, Lior Wolf
Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer. CoRR (2020)
Tomer Galanti, Lior Wolf
Comparing the Parameter Complexity of Hypernetworks and the Embedding-Based Alternative. CoRR (2020)
Etai Littwin, Tomer Galanti, Lior Wolf
On the Optimization Dynamics of Wide Hypernetworks. CoRR (2020)
Lior Wolf, Sagie Benaim, Tomer Galanti
Unsupervised Learning of the Set of Local Maxima. CoRR (2020)
Yaniv Benny, Tomer Galanti, Sagie Benaim, Lior Wolf
Evaluation Metrics for Conditional Image Generation. CoRR (2020)
Sagie Benaim, Michael Khaitov, Tomer Galanti, Lior Wolf
Domain Intersection and Domain Difference. ICCV (2019)
Sagie Benaim, Michael Khaitov, Tomer Galanti, Lior Wolf
Domain Intersection and Domain Difference. CoRR (2019)
Ori Press, Tomer Galanti, Sagie Benaim, Lior Wolf
Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer. ICLR (Poster) (2019)
Lior Wolf, Sagie Benaim, Tomer Galanti
Unsupervised Learning of the Set of Local Maxima. ICLR (Poster) (2019)
Lior Wolf, Tomer Galanti, Tamir Hazan
A Formal Approach to Explainability. AIES (2019)
Tomer Galanti, Sagie Benaim, Lior Wolf
Generalization Bounds for Unsupervised Cross-Domain Mapping with WGANs. CoRR (2018)
Sagie Benaim, Tomer Galanti, Lior Wolf
Estimating the Success of Unsupervised Image to Image Translation. ECCV (5) (2018)
Tomer Galanti, Lior Wolf, Sagie Benaim
The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings. ICLR (Poster) (2018)
Tomer Galanti, Lior Wolf
A Theory of Output-Side Unsupervised Domain Adaptation. CoRR (2017)
Tomer Galanti, Lior Wolf
Unsupervised Learning of Semantic Mappings. CoRR (2017)
Sagie Benaim, Tomer Galanti, Lior Wolf
Maximally Distant Cross Domain Generators for Estimating Per-Sample Error. CoRR (2017)