A Theory of Output-Side Unsupervised Domain Adaptation. - Tomer Galanti; Lior Wolf (CoRR, 2017)

Unsupervised Learning of Semantic Mappings. - Tomer Galanti; Lior Wolf (CoRR, 2017)

Maximally Distant Cross Domain Generators for Estimating Per-Sample Error. - Sagie Benaim; Tomer Galanti; Lior Wolf (CoRR, 2017)

Estimating the Success of Unsupervised Image to Image Translation. - Sagie Benaim; Tomer Galanti; Lior Wolf (ECCV (5), 2018)

The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings. - Tomer Galanti; Lior Wolf; Sagie Benaim (ICLR (Poster), 2018)

Generalization Bounds for Unsupervised Cross-Domain Mapping with WGANs. - Tomer Galanti; Sagie Benaim; Lior Wolf (CoRR, 2018)

A Formal Approach to Explainability. - Lior Wolf; Tomer Galanti; Tamir Hazan (AIES, 2019)

Domain Intersection and Domain Difference. - Sagie Benaim; Michael Khaitov; Tomer Galanti; Lior Wolf (ICCV, 2019)

Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer. - Ori Press; Tomer Galanti; Sagie Benaim; Lior Wolf (ICLR (Poster), 2019)

Unsupervised Learning of the Set of Local Maxima. - Lior Wolf; Sagie Benaim; Tomer Galanti (ICLR (Poster), 2019)

On the Modularity of Hypernetworks. - Tomer Galanti; Lior Wolf (NeurIPS, 2020)

On Infinite-Width Hypernetworks. - Etai Littwin; Tomer Galanti; Lior Wolf; Greg Yang (NeurIPS, 2020)

Comparing the Parameter Complexity of Hypernetworks and the Embedding-Based Alternative. - Tomer Galanti; Lior Wolf (CoRR, 2020)

A Critical View of the Structural Causal Model. - Tomer Galanti; Ofir Nabati; Lior Wolf (CoRR, 2020)

On the Optimization Dynamics of Wide Hypernetworks. - Etai Littwin; Tomer Galanti; Lior Wolf (CoRR, 2020)

Meta Internal Learning. - Raphael Bensadoun; Shir Gur; Tomer Galanti; Lior Wolf (NeurIPS, 2021)

On random kernels of residual architectures. - Etai Littwin; Tomer Galanti; Lior Wolf (UAI, 2021)

Intersection Regularization for Extracting Semantic Attributes. - Ameen Ali; Tomer Galanti; Evgeniy Zheltonozhskiy; Chaim Baskin; Lior Wolf (CoRR, 2021)

Evaluation Metrics for Conditional Image Generation. - Yaniv Benny; Tomer Galanti; Sagie Benaim; Lior Wolf (Int. J. Comput. Vis., 2021)

Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs. - Tomer Galanti; Sagie Benaim; Lior Wolf (J. Mach. Learn. Res., 2021)

On the Emergence of Semantic Structure in Deep Learning - Tomer Galanti (2021)

Weakly Supervised Discovery of Semantic Attributes. - Ameen Ali; Tomer Galanti; Evgenii Zheltonozhskii; Chaim Baskin; Lior Wolf (CLeaR, 2022)

Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models. - Chenfeng Xu; Shijia Yang; Tomer Galanti; Bichen Wu; Xiangyu Yue 001; Bohan Zhai; Wei Zhan; Peter Vajda; Kurt Keutzer; Masayoshi Tomizuka (ECCV (37), 2022)

On the Role of Neural Collapse in Transfer Learning. - Tomer Galanti; András György 001; Marcus Hutter (ICLR, 2022)

A Note on the Implicit Bias Towards Minimal Depth of Deep Neural Networks. - Tomer Galanti (CoRR, 2022)

SGD Noise and Implicit Low-Rank Bias in Deep Neural Networks. - Tomer Galanti; Tomaso A. Poggio (CoRR, 2022)

Generalization Bounds for Transfer Learning with Pretrained Classifiers. - Tomer Galanti; András György 001; Marcus Hutter (CoRR, 2022)

Feature learning in deep classifiers through Intermediate Neural Collapse. - Akshay Rangamani; Marius Lindegaard; Tomer Galanti; Tomaso A. Poggio (ICML, 2023)

Reverse Engineering Self-Supervised Learning. - Ido Ben-Shaul; Ravid Shwartz-Ziv; Tomer Galanti; Shai Dekel; Yann LeCun (NeurIPS, 2023)

Norm-based Generalization Bounds for Sparse Neural Networks. - Tomer Galanti; Mengjia Xu; Liane Galanti; Tomaso A. Poggio (NeurIPS, 2023)

Norm-based Generalization Bounds for Compositionally Sparse Neural Networks. - Tomer Galanti; Mengjia Xu; Liane Galanti; Tomaso A. Poggio (CoRR, 2023)

The Probabilistic Stability of Stochastic Gradient Descent. - Liu Ziyin 001; Botao Li; Tomer Galanti; Masahito Ueda (CoRR, 2023)

Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions. - Ido Ben-Shaul; Tomer Galanti; Shai Dekel (Trans. Mach. Learn. Res., 2023)

Comparative Generalization Bounds for Deep Neural Networks. - Tomer Galanti; Liane Galanti; Ido Ben-Shaul (Trans. Mach. Learn. Res., 2023)

Distributed Speculative Inference of Large Language Models is Provably Faster. - Nadav Timor; Jonathan Mamou; Oren Pereg; Moshe Berchansky; Daniel Korat; Moshe Wasserblat; Tomer Galanti; Michal Gordon; David Harel (ENLSP, 2024)

On the Power of Decision Trees in Auto-Regressive Language Modeling. - Yulu Gan; Tomer Galanti; Tomaso A. Poggio; Eran Malach (NeurIPS, 2024)

Distributed Speculative Inference of Large Language Models. - Nadav Timor; Jonathan Mamou; Daniel Korat; Moshe Berchansky; Oren Pereg; Moshe Wasserblat; Tomer Galanti; Michal Gordon; David Harel (CoRR, 2024)

The Fair Language Model Paradox. - Andrea Pinto; Tomer Galanti; Randall Balestriero (CoRR, 2024)

SGD with Weight Decay Secretly Minimizes the Ranks of Your Neural Networks. - Tomer Galanti; Zachary S. Siegel; Aparna Gupte; Tomaso A. Poggio (CPAL, 2025)

Formation of Representations in Neural Networks. - Liu Ziyin 001; Isaac L. Chuang; Tomer Galanti; Tomaso A. Poggio (ICLR, 2025)

Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference. - Nadav Timor; Jonathan Mamou; Daniel Korat; Moshe Berchansky; Oren Pereg; Moshe Wasserblat; Tomer Galanti; Michal Gordon-Kiwkowitz; David Harel (ICLR, 2025)

Centered Self-attention Layers. - Ameen Ali; Tomer Galanti; Lior Wolf (SCIA (1), 2025)

DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization. - Gang Li; Ming Lin; Tomer Galanti; Zhengzhong Tu; Tianbao Yang (CoRR, 2025)

Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning. - Achleshwar Luthra; Tianbao Yang; Tomer Galanti (CoRR, 2025)

On the Alignment Between Supervised and Self-Supervised Contrastive Learning. - Achleshwar Luthra; Priyadarsi Mishra; Tomer Galanti (CoRR, 2025)

LLM-ERM: Sample-Efficient Program Learning via LLM-Guided Search. - Shivam Singhal; Eran Malach; Tomaso A. Poggio; Tomer Galanti (CoRR, 2025)

Scalable Principal-Agent Contract Design via Gradient-Based Optimization. - Tomer Galanti; Aarya Bookseller; Korok Ray (CoRR, 2025)