Yuval Kluger - RankMe

80 papers A* 14A 5Misc 1Journal 56Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Dual Diffusion for Unified Image Generation and Understanding. CVPR Zijie Li, Henry Li, Yichun Shi, Amir Barati Farimani, Yuval Kluger, Linjie Yang, Peng Wang
2025	J	`jnl`	Dual Diffusion for Unified Image Generation and Understanding. CoRR Zijie Li, Henry Li, Yichun Shi, Amir Barati Farimani, Yuval Kluger, Linjie Yang, Peng Wang
2025	J	`jnl`	Euclidean Distance Deflation Under High-Dimensional Heteroskedastic Noise. CoRR Keyi Li, Yuval Kluger, Boris Landa
2025	J	`jnl`	Injecting Measurement Information Yields a Fast and Noise-Robust Diffusion-Based Inverse Problem Solver. CoRR Jonathan Patsenker, Henry Li, Myeongseob Ko, Ruoxi Jia, Yuval Kluger
2025	J	`jnl`	Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps. CoRR Henry Li, Ronen Basri, Yuval Kluger
2025	A*	`conf`	Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data. ICML Erez Peterfreund, Ofir Lindenbaum, Yuval Kluger, Boris Landa
2025	J	`jnl`	Supervised fine-tuning of pre-trained antibody language models improves antigen specificity prediction. PLoS Comput. Biol. Meng Wang, Jonathan Patsenker, Henry Li, Yuval Kluger, Steven H. Kleinstein
2025	J	`jnl`	Understanding and Enhancing Mask-Based Pretraining towards Universal Representations. CoRR Mingze Dong, Leda Wang, Yuval Kluger
2024	J	`jnl`	Entropic Optimal Transport Eigenmaps for Nonlinear Alignment and Joint Embedding of High-Dimensional Datasets. CoRR Boris Landa, Yuval Kluger, Rong Ma
2024	Misc	`conf`	Hyperbolic Diffusion Procrustes Analysis for Intrinsic Representation of Hierarchical Data Sets. ICASSP Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon
2024	A*	`conf`	Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps. ICLR Henry Li, Ronen Basri, Yuval Kluger
2024	J	`jnl`	Three-Dimensional Reconstruction Pre-Training as a Prior to Improve Robustness to Adversarial Attacks and Spurious Correlation. Entropy Yutaro Yamada, Fred Weiying Zhang, Yuval Kluger, Ilker Yildirim
2024	A	`conf`	Transductive and Inductive Outlier Detection with Robust Autoencoders. UAI Ofir Lindenbaum, Yariv Aizenbud, Yuval Kluger
2023	J	`jnl`	Comprehensive visualization of cell-cell interactions in single-cell and spatial transcriptomics with NICHES. Bioinform. Micha Sam Brickman Raredon, Junchen Yang, Neeharika Kothapalli, Wesley Lewis, Naftali Kaminski, Laura E. Niklason, Yuval Kluger
2023	J	`jnl`	Exponential weight averaging as damped harmonic motion. CoRR Jonathan Patsenker, Henry Li, Yuval Kluger
2023	A*	`conf`	Few-Sample Feature Selection via Feature Manifold Learning. ICML David Cohen, Tal Shnitzer, Yuval Kluger, Ronen Talmon
2023	A*	`conf`	GEASS: Neural causal feature selection for high-dimensional biological data. ICLR Mingze Dong, Yuval Kluger
2023	J	`jnl`	Multi-modal Differentiable Unsupervised Feature Selection. CoRR Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe
2023	A	`conf`	Multi-modal differentiable unsupervised feature selection. UAI Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe
2023	A*	`conf`	Towards Understanding and Reducing Graph Structural Noise for GNNs. ICML Mingze Dong, Yuval Kluger
2022	J	`jnl`	Autoregressive Generative Modeling with Noise Conditional Maximum Likelihood Estimation. CoRR Henry Li, Yuval Kluger
2022	J	`jnl`	Biwhitening Reveals the Rank of a Count Matrix. SIAM J. Math. Data Sci. Boris Landa, Thomas T. C. K. Zhang, Yuval Kluger
2022	A	`conf`	Crowdsourcing Regression: A Spectral Approach. AISTATS Yaniv Tenzer, Omer Dror, Boaz Nadler, Erhan Bilal, Yuval Kluger
2022	J	`jnl`	Deep unsupervised feature selection by discarding nuisance and correlated features. Neural Networks Uri Shaham, Ofir Lindenbaum, Jonathan Svirsky, Yuval Kluger
2022	A*	`conf`	L0-Sparse Canonical Correlation Analysis. ICLR Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger
2022	A*	`conf`	Locally Sparse Neural Networks for Tabular Biomedical Data. ICML Junchen Yang, Ofir Lindenbaum, Yuval Kluger
2022	J	`jnl`	ManiFeSt: Manifold-based Feature Selection for Small Data Sets. CoRR David Cohen, Tal Shnitzer, Yuval Kluger, Ronen Talmon
2022	A*	`conf`	Neural Inverse Transform Sampler. ICML Henry Li, Yuval Kluger
2022	J	`jnl`	Neural Inverse Transform Sampler. CoRR Henry Li, Yuval Kluger
2022	J	`jnl`	On the efficient evaluation of the azimuthal Fourier components of the Green's function for Helmholtz's equation in cylindrical coordinates. J. Comput. Phys. James Garritano, Yuval Kluger, Vladimir Rokhlin, Kirill Serkh
2021	J	`jnl`	Biwhitening Reveals the Rank of a Count Matrix. CoRR Boris Landa, Thomas T. C. K. Zhang, Yuval Kluger
2021	J	`jnl`	Deep Unsupervised Feature Selection by Discarding Nuisance and Correlated Features. CoRR Uri Shaham, Ofir Lindenbaum, Jonathan Svirsky, Yuval Kluger
2021	A*	`conf`	Differentiable Unsupervised Feature Selection based on a Gated Laplacian. NeurIPS Ofir Lindenbaum, Uri Shaham, Erez Peterfreund, Jonathan Svirsky, Nicolas Casey, Yuval Kluger
2021	J	`jnl`	Doubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise. SIAM J. Math. Data Sci. Boris Landa, Ronald R. Coifman, Yuval Kluger
2021	J	`jnl`	Graph of graphs analysis for multiplexed data with application to imaging mass cytometry. PLoS Comput. Biol. Ya-Wei Eileen Lin, Tal Shnitzer, Ronen Talmon, Franz Villarroel-Espindola, Shruti Desai, Kurt A. Schalper, Yuval Kluger
2021	A*	`conf`	Hyperbolic Procrustes Analysis Using Riemannian Geometry. NeurIPS Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon
2021	J	`jnl`	Locally Sparse Networks for Interpretable Predictions. CoRR Junchen Yang, Ofir Lindenbaum, Yuval Kluger
2021	J	`jnl`	On the Efficient Evaluation of the Azimuthal Fourier Components of the Green's Function for Helmholtz's Equation in Cylindrical Coordinates. CoRR James Garritano, Yuval Kluger, Vladimir Rokhlin, Kirill Serkh
2021	J	`jnl`	Probabilistic Robust Autoencoders for Anomaly Detection. CoRR Yariv Aizenbud, Ofir Lindenbaum, Yuval Kluger
2021	J	`jnl`	Spectral Neighbor Joining for Reconstruction of Latent Tree Models. SIAM J. Math. Data Sci. Ariel Jaffe, Noah Amsel, Yariv Aizenbud, Boaz Nadler, Joseph T. Chang, Yuval Kluger
2021	J	`jnl`	Spectral Top-Down Recovery of Latent Tree Models. CoRR Yariv Aizenbud, Ariel Jaffe, Meng Wang, Amber Hu, Noah Amsel, Boaz Nadler, Joseph T. Chang, Yuval Kluger
2020	J	`jnl`	Deep Gated Canonical Correlation Analysis. CoRR Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger
2020	J	`jnl`	Doubly-Stochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noise. CoRR Boris Landa, Ronald R. Coifman, Yuval Kluger
2020	A*	`conf`	Feature Selection using Stochastic Gates. ICML Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger
2020	J	`jnl`	Let the Data Choose its Features: Differentiable Unsupervised Feature Selection. CoRR Ofir Lindenbaum, Uri Shaham, Jonathan Svirsky, Erez Peterfreund, Yuval Kluger
2020	J	`jnl`	Randomized near-neighbor graphs, giant components and applications in data science. J. Appl. Probab. Ariel Jaffe, Yuval Kluger, George C. Linderman, Gal Mishne, Stefan Steinerberger
2020	J	`jnl`	Spectral neighbor joining for reconstruction of latent tree models. CoRR Ariel Jaffe, Noah Amsel, Boaz Nadler, Joseph T. Chang, Yuval Kluger
2020	J	`jnl`	The Spectral Underpinning of word2vec. CoRR Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum, Jonathan Patsenker, Erez Peterfreund, Stefan Steinerberger
2020	J	`jnl`	The Spectral Underpinning of word2vec. Frontiers Appl. Math. Stat. Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum, Jonathan Patsenker, Erez Peterfreund, Stefan Steinerberger
2019	—	`conf`	Heavy-Tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations. ECML/PKDD (1) Dmitry Kobak, George C. Linderman, Stefan Steinerberger, Yuval Kluger, Philipp Berens
2019	J	`jnl`	Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations. CoRR Dmitry Kobak, George C. Linderman, Stefan Steinerberger, Yuval Kluger, Philipp Berens
2018	J	`jnl`	Data-Driven Tree Transforms and Metrics. IEEE Trans. Signal Inf. Process. over Networks Gal Mishne, Ronen Talmon, Israel Cohen, Ronald R. Coifman, Yuval Kluger
2018	J	`jnl`	Deep supervised feature selection using Stochastic Gates. CoRR Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger
2018	J	`jnl`	Defending against Adversarial Images using Basis Functions Transformations. CoRR Uri Shaham, James Garritano, Yutaro Yamada, Ethan Weinberger, Alex Cloninger, Xiuyuan Cheng, Kelly P. Stanton, Yuval Kluger
2018	A*	`conf`	Learning Binary Latent Variable Models: A Tensor Eigenpair Approach. ICML Ariel Jaffe, Roi Weiss, Shai Carmi, Yuval Kluger, Boaz Nadler
2018	J	`jnl`	Randomized algorithms for distributed computation of principal component analysis and singular value decomposition. Adv. Comput. Math. Huamin Li, Yuval Kluger, Mark Tygert
2018	—	`conf`	SpectralNet: Spectral Clustering using Deep Neural Networks. ICLR (Poster) Uri Shaham, Kelly P. Stanton, Henry Li, Ronen Basri, Boaz Nadler, Yuval Kluger
2018	J	`jnl`	SpectralNet: Spectral Clustering using Deep Neural Networks. CoRR Uri Shaham, Kelly P. Stanton, Henry Li, Boaz Nadler, Ronen Basri, Yuval Kluger
2017	J	`jnl`	Algorithm 971: An Implementation of a Randomized Algorithm for Principal Component Analysis. ACM Trans. Math. Softw. Huamin Li, George C. Linderman, Arthur Szlam, Kelly P. Stanton, Yuval Kluger, Mark Tygert
2017	J	`jnl`	Data-Driven Tree Transforms and Metrics. CoRR Gal Mishne, Ronen Talmon, Israel Cohen, Ronald R. Coifman, Yuval Kluger
2017	J	`jnl`	Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding. CoRR George C. Linderman, Manas Rachh, Jeremy G. Hoskins, Stefan Steinerberger, Yuval Kluger
2017	J	`jnl`	Gating mass cytometry data by deep learning. Bioinform. Huamin Li, Uri Shaham, Kelly P. Stanton, Yi Yao, Ruth R. Montgomery, Yuval Kluger
2017	J	`jnl`	Randomized Near Neighbor Graphs, Giant Components, and Applications in Data Science. CoRR George C. Linderman, Gal Mishne, Yuval Kluger, Stefan Steinerberger
2017	J	`jnl`	Removal of batch effects using distribution-matching residual networks. Bioinform. Uri Shaham, Kelly P. Stanton, Jun Zhao, Huamin Li, Khadir Raddassi, Ruth R. Montgomery, Yuval Kluger
2017	J	`jnl`	Unsupervised Ensemble Regression. CoRR Omer Dror, Boaz Nadler, Erhan Bilal, Yuval Kluger
2016	A*	`conf`	A Deep Learning Approach to Unsupervised Ensemble Learning. ICML Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph T. Chang, Yuval Kluger
2016	J	`jnl`	A Deep Learning Approach to Unsupervised Ensemble Learning. CoRR Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph T. Chang, Yuval Kluger
2016	J	`jnl`	Deep Survival: A Deep Cox Proportional Hazards Network. CoRR Jared Katzman, Uri Shaham, Alexander Cloninger, Jonathan Bates, Tingting Jiang, Yuval Kluger
2016	J	`jnl`	Randomized algorithms for distributed computation of principal component analysis and singular value decomposition. CoRR Huamin Li, Yuval Kluger, Mark Tygert
2016	A	`conf`	Unsupervised Ensemble Learning with Dependent Classifiers. AISTATS Ariel Jaffe, Ethan Fetaya, Boaz Nadler, Tingting Jiang, Yuval Kluger
2015	A	`conf`	Estimating the accuracies of multiple classifiers without labeled data. AISTATS Ariel Jaffe, Boaz Nadler, Yuval Kluger
2015	J	`jnl`	Unsupervised Ensemble Learning with Dependent Classifiers. CoRR Ariel Jaffe, Ethan Fetaya, Boaz Nadler, Tingting Jiang, Yuval Kluger
2014	J	`jnl`	An implementation of a randomized algorithm for principal component analysis. CoRR Arthur Szlam, Yuval Kluger, Mark Tygert
2014	J	`jnl`	Estimating the Accuracies of Multiple Classifiers Without Labeled Data. CoRR Ariel Jaffe, Boaz Nadler, Yuval Kluger
2013	J	`jnl`	The student's dilemma: ranking and improving prediction at test time without access to training data CoRR Fabio Parisi, Francesco Strino, Boaz Nadler, Yuval Kluger
2007	—	`conf`	Inter- and Intra-Combinatorial Regulation by Transcriptions Factors and MicroRNAs. BIOCOMP Yiming Zhou, John Ferguson, Joseph T. Chang, Yuval Kluger
2006	—	`conf`	Association between pathways in regulatory networks. EMBC Yuval Kluger, Harriet Kluger, David Tuck
2006	J	`jnl`	Characterizing disease states from topological properties of transcriptional regulatory networks. BMC Bioinform. David Tuck, Harriet Kluger, Yuval Kluger
2006	J	`jnl`	Unraveling condition specific gene transcriptional regulatory networks in Saccharomyces cerevisiae. BMC Bioinform. Hyunsoo Kim, William Hu, Yuval Kluger
2001	J	`jnl`	SPINE: an integrated tracking database and data mining approach for identifying feasible targets in high-throughput structural proteomics. Nucleic Acids Res. Paul Bertone, Yuval Kluger, Ning Lan, Deyou Zheng, Dinesh Christendat, Adelinda Yee, Aled M. Edwards, Cheryl H. Arrowsmith, Gaetano T. Montelione, Mark Gerstein