Kluger, Yuval

25 publications

CVPR 2025 Dual Diffusion for Unified Image Generation and Understanding Zijie Li, Henry Li, Yichun Shi, Amir Barati Farimani, Yuval Kluger, Linjie Yang, Peng Wang

ICML 2025 Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data Erez Peterfreund, Ofir Lindenbaum, Yuval Kluger, Boris Landa

NeurIPS 2025 Understanding and Enhancing Mask-Based Pretraining Towards Universal Representations Mingze Dong, Leda Wang, Yuval Kluger

ICLR 2024 Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-Preserving Maps Henry Li, Ronen Basri, Yuval Kluger

UAI 2024 Transductive and Inductive Outlier Detection with Robust Autoencoders Ofir Lindenbaum, Yariv Aizenbud, Yuval Kluger

ICMLW 2023 Exponential Weight Averaging as Damped Harmonic Motion Jonathan Patsenker, Henry Li, Yuval Kluger

ICML 2023 Few-Sample Feature Selection via Feature Manifold Learning David Cohen, Tal Shnitzer, Yuval Kluger, Ronen Talmon

ICLR 2023 GEASS: Neural Causal Feature Selection for High-Dimensional Biological Data Mingze Dong, Yuval Kluger

UAI 2023 Multi-Modal Differentiable Unsupervised Feature Selection Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe

ICML 2023 Towards Understanding and Reducing Graph Structural Noise for GNNs Mingze Dong, Yuval Kluger

AISTATS 2022 Crowdsourcing Regression: A Spectral Approach Yaniv Tenzer, Omer Dror, Boaz Nadler, Erhan Bilal, Yuval Kluger

ICLR 2022 L0-Sparse Canonical Correlation Analysis Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger

ICML 2022 Locally Sparse Neural Networks for Tabular Biomedical Data Junchen Yang, Ofir Lindenbaum, Yuval Kluger

ICML 2022 Neural Inverse Transform Sampler Henry Li, Yuval Kluger

NeurIPSW 2022 Noise-Conditional Maximum Likelihood Estimation with Score-Based Sampling Henry Li, Yuval Kluger

NeurIPS 2021 Differentiable Unsupervised Feature Selection Based on a Gated Laplacian Ofir Lindenbaum, Uri Shaham, Erez Peterfreund, Jonathan Svirsky, Nicolas Casey, Yuval Kluger

NeurIPSW 2021 Exploiting 3D Shape Bias Towards Robust Vision Yutaro Yamada, Yuval Kluger, Sahand Negahban, Ilker Yildirim

NeurIPS 2021 Hyperbolic Procrustes Analysis Using Riemannian Geometry Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon

ICML 2020 Feature Selection Using Stochastic Gates Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger

ECML-PKDD 2019 Heavy-Tailed Kernels Reveal a Finer Cluster Structure in T-SNE Visualisations Dmitry Kobak, George C. Linderman, Stefan Steinerberger, Yuval Kluger, Philipp Berens

ICML 2018 Learning Binary Latent Variable Models: A Tensor Eigenpair Approach Ariel Jaffe, Roi Weiss, Boaz Nadler, Shai Carmi, Yuval Kluger

ICLR 2018 SpectralNet: Spectral Clustering Using Deep Neural Networks Uri Shaham, Kelly Stanton, Henry Li, Ronen Basri, Boaz Nadler, Yuval Kluger

ICML 2016 A Deep Learning Approach to Unsupervised Ensemble Learning Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph Chang, Yuval Kluger

AISTATS 2016 Unsupervised Ensemble Learning with Dependent Classifiers Ariel Jaffe, Ethan Fetaya, Boaz Nadler, Tingting Jiang, Yuval Kluger

AISTATS 2015 Estimating the Accuracies of Multiple Classifiers Without Labeled Data Ariel Jaffe, Boaz Nadler, Yuval Kluger