Ivan Dokmanic - RankMe

132 papers A* 11A 1Misc 25Journal 84Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Flowers: A Warp Drive for Neural PDE Solvers. CoRR Till Muser, Alexandra Spitzer, Matti Lassas, Maarten V. de Hoop, Ivan Dokmanic
2025	J	`jnl`	GLIMPSE: Generalized Locality for Scalable and Robust CT. IEEE Trans. Medical Imaging AmirEhsan Khorashadizadeh, Valentin Debarnot, Tianlin Liu, Ivan Dokmanic
2025	J	`jnl`	Ice-Tide: Implicit Cryo-ET Imaging and Deformation Estimation. IEEE Trans. Computational Imaging Valentin Debarnot, Vinith Kishore, Ricardo D. Righetto, Ivan Dokmanic
2025	A*	`conf`	Joint Graph Rewiring and Feature Denoising via Spectral Resonance. ICLR Jonas Linkerhägner, Cheng Shi, Ivan Dokmanic
2025	J	`jnl`	LoFi: Neural Local Fields for Scalable Image Reconstruction. IEEE Trans. Computational Imaging AmirEhsan Khorashadizadeh, Tobías I. Liaudat, Tianlin Liu, Jason D. McEwen, Ivan Dokmanic
2025	J	`jnl`	Neural equilibria for long-term prediction of nonlinear conservation laws. CoRR Jose Antonio Lara Benitez, Junyi Guo, Kareem Hegazy, Ivan Dokmanic, Michael W. Mahoney, Maarten V. de Hoop
2025	J	`jnl`	Rates and architectures for learning geometrically non-trivial operators. CoRR T. Mitchell Roddenberry, Leo Tzou, Ivan Dokmanic, Maarten V. de Hoop, Richard G. Baraniuk
2024	A*	`conf`	A Graph Dynamics Prior for Relational Inference. AAAI Liming Pan, Cheng Shi, Ivan Dokmanic
2024	J	`jnl`	A spring-block theory of feature learning in deep neural networks. CoRR Cheng Shi, Liming Pan, Ivan Dokmanic
2024	J	`jnl`	Differentiable Uncalibrated Imaging. IEEE Trans. Computational Imaging Sidharth Gupta, Konik Kothari, Valentin Debarnot, Ivan Dokmanic
2024	J	`jnl`	Editorial Introduction to the Special Issue Seeking Low-Dimensionality in Deep Neural Networks (SLowDNN). IEEE J. Sel. Top. Signal Process. Yi Ma, Yuejie Chi, Ivan Dokmanic, Bihan Wen, John N. Wright, Zhihui Zhu
2024	J	`jnl`	GLIMPSE: Generalized Local Imaging with MLPs. CoRR AmirEhsan Khorashadizadeh, Valentin Debarnot, Tianlin Liu, Ivan Dokmanic
2024	J	`jnl`	Joint Graph Rewiring and Feature Denoising via Spectral Resonance. CoRR Jonas Linkerhägner, Cheng Shi, Ivan Dokmanic
2024	J	`jnl`	LoFi: Scalable Local Image Reconstruction with Implicit Neural Representation. CoRR AmirEhsan Khorashadizadeh, Tobías I. Liaudat, Tianlin Liu, Jason D. McEwen, Ivan Dokmanic
2024	J	`jnl`	SeisLM: a Foundation Model for Seismic Waveforms. CoRR Tianlin Liu, Jannes Münchmeyer, Laura Laurenti, Chris Marone, Maarten V. de Hoop, Ivan Dokmanic
2024	J	`jnl`	WaveBench: Benchmarking Data-driven Solvers for Linear Wave Propagation PDEs. Trans. Mach. Learn. Res. Tianlin Liu, Jose Antonio Lara Benitez, Florian Faucher, AmirEhsan Khorashadizadeh, Maarten V. de Hoop, Ivan Dokmanic
2023	J	`jnl`	A Dynamical Graph Prior for Relational Inference. CoRR Liming Pan, Cheng Shi, Ivan Dokmanic
2023	A*	`conf`	A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression. NeurIPS Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, Ivan Dokmanic, David Belius
2023	J	`jnl`	A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression. CoRR Tin Sum Cheng, Aurélien Lucchi, Ivan Dokmanic, Anastasis Kratsios, David Belius
2023	J	`jnl`	A Transfer Principle: Universal Approximators Between Metric Spaces From Euclidean Universal Approximators. CoRR Anastasis Kratsios, Chong Liu, Matti Lassas, Maarten V. de Hoop, Ivan Dokmanic
2023	J	`jnl`	Conditional Injective Flows for Bayesian Imaging. IEEE Trans. Computational Imaging AmirEhsan Khorashadizadeh, Konik Kothari, Leonardo Salsi, Ali Aghababaei Harandi, Maarten V. de Hoop, Ivan Dokmanic
2023	J	`jnl`	Deep Injective Prior for Inverse Scattering. CoRR AmirEhsan Khorashadizadeh, Sepehr Eskandari, Vahid Khorashadi-Zadeh, Ivan Dokmanic
2023	A*	`conf`	FunkNN: Neural Interpolation for Functional Generation. ICLR AmirEhsan Khorashadizadeh, Anadi Chaman, Valentin Debarnot, Ivan Dokmanic
2023	J	`jnl`	Harpa: High-Rate Phase Association with Travel Time Neural Fields. CoRR Cheng Shi, Maarten V. de Hoop, Ivan Dokmanic
2023	J	`jnl`	Injectivity of ReLU networks: perspectives from statistical physics. CoRR Antoine Maillard, Afonso S. Bandeira, David Belius, Ivan Dokmanic, Shuta Nakajima
2023	Misc	`conf`	Joint Cryo-ET Alignment and Reconstruction with Neural Deformation Fields. ICASSP Valentin Debarnot, Sidharth Gupta, Konik Kothari, Ivan Dokmanic
2023	J	`jnl`	Localizing Unsynchronized Sensors With Unknown Sources. IEEE Trans. Signal Process. Dalia El Badawy, Viktor Larsson, Marc Pollefeys, Ivan Dokmanic
2023	J	`jnl`	Orthogonal Matrix Retrieval with Spatial Consensus for 3D Unknown View Tomography. SIAM J. Imaging Sci. Shuai Huang, Mona Zehni, Ivan Dokmanic, Zhizhen Zhao
2023	J	`jnl`	Small Transformers Compute Universal Metric Embeddings. J. Mach. Learn. Res. Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanic
2022	J	`jnl`	Conditional Injective Flows for Bayesian Imaging. CoRR AmirEhsan Khorashadizadeh, Konik Kothari, Leonardo Salsi, Ali Aghababaei Harandi, Maarten V. de Hoop, Ivan Dokmanic
2022	J	`jnl`	Deep Invertible Approximation of Topologically Rich Maps between Manifolds. CoRR Michael Puthawala, Matti Lassas, Ivan Dokmanic, Pekka Pankka, Maarten V. de Hoop
2022	J	`jnl`	Deep Variational Inverse Scattering. CoRR AmirEhsan Khorashadizadeh, Ali Aghababaei Harandi, Tin Vlasic, Hieu Nguyen, Ivan Dokmanic
2022	J	`jnl`	Differentiable Uncalibrated Imaging. CoRR Sidharth Gupta, Konik Kothari, Valentin Debarnot, Ivan Dokmanic
2022	J	`jnl`	FunkNN: Neural Interpolation for Functional Generation. CoRR AmirEhsan Khorashadizadeh, Anadi Chaman, Valentin Debarnot, Ivan Dokmanic
2022	J	`jnl`	Globally Injective ReLU Networks. J. Mach. Learn. Res. Michael Puthawala, Konik Kothari, Matti Lassas, Ivan Dokmanic, Maarten V. de Hoop
2022	—	`conf`	Implicit Neural Representation for Mesh-Free Inverse Obstacle Scattering. IEEECONF Tin Vlasic, Hieu Nguyen, AmirEhsan Khorashadizadeh, Ivan Dokmanic
2022	J	`jnl`	Implicit Neural Representation for Mesh-Free Inverse Obstacle Scattering. CoRR Tin Vlasic, Hieu Nguyen, AmirEhsan Khorashadizadeh, Ivan Dokmanic
2022	J	`jnl`	Learning Multiscale Convolutional Dictionaries for Image Reconstruction. IEEE Trans. Computational Imaging Tianlin Liu, Anadi Chaman, David Belius, Ivan Dokmanic
2022	A*	`conf`	Neural Link Prediction with Walk Pooling. ICLR Liming Pan, Cheng Shi, Ivan Dokmanic
2022	J	`jnl`	Orthogonal Matrix Retrieval with Spatial Consensus for 3D Unknown-View Tomography. CoRR Shuai Huang, Mona Zehni, Ivan Dokmanic, Zhizhen Zhao
2022	J	`jnl`	Small Transformers Compute Universal Metric Embeddings. CoRR Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanic
2022	J	`jnl`	Statistical Mechanics of Generalization In Graph Convolution Networks. CoRR Cheng Shi, Liming Pan, Hong Hu, Ivan Dokmanic
2022	J	`jnl`	The Fastest $\ell _{1, \infty }$ℓ1, ∞ Prox in the West. IEEE Trans. Pattern Anal. Mach. Intell. Benjamín Béjar Haro, Ivan Dokmanic, René Vidal
2022	J	`jnl`	Total Least Squares Phase Retrieval. IEEE Trans. Signal Process. Sidharth Gupta, Ivan Dokmanic
2022	A*	`conf`	Universal Approximation Under Constraints is Possible with Transformers. ICLR Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, Ivan Dokmanic
2022	A*	`conf`	Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows. ICML Michael Puthawala, Matti Lassas, Ivan Dokmanic, Maarten V. de Hoop
2021	J	`jnl`	Neural Link Prediction with Walk Pooling. CoRR Liming Pan, Cheng Shi, Ivan Dokmanic
2021	J	`jnl`	On Procrustes Analysis in Hyperbolic Space. IEEE Signal Process. Lett. Puoya Tabaghi, Ivan Dokmanic
2021	J	`jnl`	Reconstructing Point Sets From Distance Distributions. IEEE Trans. Signal Process. Shuai Huang, Ivan Dokmanic
2021	—	`conf`	Truly Shift-Equivariant Convolutional Neural Networks with Adaptive Polyphase Upsampling. ACSCC Anadi Chaman, Ivan Dokmanic
2021	A*	`conf`	Truly Shift-Invariant Convolutional Neural Networks. CVPR Anadi Chaman, Ivan Dokmanic
2021	J	`jnl`	Truly shift-equivariant convolutional neural networks with adaptive polyphase upsampling. CoRR Anadi Chaman, Ivan Dokmanic
2021	J	`jnl`	Trumpets: Injective Flows for Inference and Inverse Problems. CoRR Konik Kothari, AmirEhsan Khorashadizadeh, Maarten V. de Hoop, Ivan Dokmanic
2021	A	`conf`	Trumpets: Injective flows for inference and inverse problems. UAI Konik Kothari, AmirEhsan Khorashadizadeh, Maarten V. de Hoop, Ivan Dokmanic
2021	J	`jnl`	Universal Approximation Under Constraints is Possible with Transformers. CoRR Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, Ivan Dokmanic
2021	J	`jnl`	Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows. CoRR Michael Puthawala, Matti Lassas, Ivan Dokmanic, Maarten V. de Hoop
2020	Misc	`conf`	3D Unknown View Tomography Via Rotation Invariants. ICASSP Mona Zehni, Shuai Huang, Ivan Dokmanic, Zhizhen Zhao
2020	Misc	`conf`	Fast Optical System Identification by Numerical Interferometry. ICASSP Sidharth Gupta, Rémi Gribonval, Laurent Daudet, Ivan Dokmanic
2020	J	`jnl`	Geometry of Comparisons. CoRR Puoya Tabaghi, Ivan Dokmanic
2020	J	`jnl`	Globally Injective ReLU Networks. CoRR Michael Puthawala, Konik Kothari, Matti Lassas, Ivan Dokmanic, Maarten V. de Hoop
2020	A*	`conf`	Hyperbolic Distance Matrices. KDD Puoya Tabaghi, Ivan Dokmanic
2020	J	`jnl`	Hyperbolic Distance Matrices. CoRR Puoya Tabaghi, Ivan Dokmanic
2020	J	`jnl`	Interpreting U-Nets via Task-Driven Multiscale Dictionary Learning. CoRR Tianlin Liu, Anadi Chaman, David Belius, Ivan Dokmanic
2020	J	`jnl`	Kinetic Euclidean Distance Matrices. IEEE Trans. Signal Process. Puoya Tabaghi, Ivan Dokmanic, Martin Vetterli
2020	A*	`conf`	Learning the Geometry of Wave-Based Imaging. NeurIPS Konik Kothari, Maarten V. de Hoop, Ivan Dokmanic
2020	J	`jnl`	Learning the geometry of wave-based imaging. CoRR Konik Kothari, Maarten V. de Hoop, Ivan Dokmanic
2020	J	`jnl`	Shapes From Echoes: Uniqueness From Point-to-Plane Distance Matrices. IEEE Trans. Signal Process. Miranda Krekovic, Ivan Dokmanic, Martin Vetterli
2020	J	`jnl`	Solving Complex Quadratic Systems With Full-Rank Random Matrices. IEEE Trans. Signal Process. Shuai Huang, Sidharth Gupta, Ivan Dokmanic
2020	J	`jnl`	Truly shift-invariant convolutional neural networks. CoRR Anadi Chaman, Ivan Dokmanic
2019	J	`jnl`	Concentration of the Frobenius Norm of Generalized Matrix Inverses. SIAM J. Matrix Anal. Appl. Ivan Dokmanic, Rémi Gribonval
2019	—	`conf`	Distance retrieval from unknown view tomography of 2D point sources. Computational Imaging Mona Zehni, Shuai Huang, Ivan Dokmanic, Zhizhen Zhao
2019	A*	`conf`	Don't take it lightly: Phasing optical random projections with unknown operators. NeurIPS Sidharth Gupta, Rémi Gribonval, Laurent Daudet, Ivan Dokmanic
2019	J	`jnl`	Don't take it lightly: Phasing optical random projections with unknown operators. CoRR Sidharth Gupta, Rémi Gribonval, Laurent Daudet, Ivan Dokmanic
2019	Misc	`conf`	Geometric Invariants for Sparse Unknown View Tomography. ICASSP Mona Zehni, Shuai Huang, Ivan Dokmanic, Zhizhen Zhao
2019	J	`jnl`	Learning Schatten-Von Neumann Operators. CoRR Puoya Tabaghi, Maarten V. de Hoop, Ivan Dokmanic
2019	Misc	`conf`	Multipath-enabled Private Audio with Noise. ICASSP Anadi Chaman, Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanic
2019	Misc	`conf`	On the Move: Localization with Kinetic Euclidean Distance Matrices. ICASSP Puoya Tabaghi, Ivan Dokmanic, Martin Vetterli
2019	J	`jnl`	Permutations Unlabeled Beyond Sampling Unknown. IEEE Signal Process. Lett. Ivan Dokmanic
2019	—	`conf`	Random mesh projectors for inverse problems. ICLR (Poster) Konik Kothari, Sidharth Gupta, Maarten V. de Hoop, Ivan Dokmanic
2019	J	`jnl`	Shapes from Echoes: Uniqueness from Point-to-Plane Distance Matrices. CoRR Miranda Krekovic, Ivan Dokmanic, Martin Vetterli
2019	Misc	`conf`	Solving Complex Quadratic Equations with Full-rank Random Gaussian Matrices. ICASSP Shuai Huang, Sidharth Gupta, Ivan Dokmanic
2019	J	`jnl`	Solving Complex Quadratic Systems with Full-Rank Random Matrices. CoRR Shuai Huang, Sidharth Gupta, Ivan Dokmanic
2019	J	`jnl`	The fastest 𝓁 CoRR Benjamín Béjar Haro, Ivan Dokmanic, René Vidal
2018	—	`conf`	Cocktails, but no Party: Multipath-Enabled Private Audio. IWAENC Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanic
2018	J	`jnl`	Cocktails, but no party: multipath-enabled private audio. CoRR Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanic
2018	J	`jnl`	Concentration of the Frobenius norms of pseudoinverses. CoRR Ivan Dokmanic, Rémi Gribonval
2018	J	`jnl`	Deep Mesh Projectors for Inverse Problems. CoRR Sidharth Gupta, Konik Kothari, Maarten V. de Hoop, Ivan Dokmanic
2018	J	`jnl`	Direction of Arrival With One Microphone, a Few LEGOs, and Non-Negative Matrix Factorization. IEEE ACM Trans. Audio Speech Lang. Process. Dalia El Badawy, Ivan Dokmanic
2018	J	`jnl`	Direction of Arrival with One Microphone, a few LEGOs, and Non-Negative Matrix Factorization. CoRR Dalia El Badawy, Ivan Dokmanic
2018	J	`jnl`	Multipath-enabled private audio with noise. CoRR Anadi Chaman, Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanic
2018	J	`jnl`	Permutations Unlabeled beyond Sampling Unknown. CoRR Ivan Dokmanic
2018	Misc	`conf`	Pyroomacoustics: A Python Package for Audio Room Simulation and Array Processing Algorithms. ICASSP Robin Scheibler, Eric Bezzam, Ivan Dokmanic
2018	J	`jnl`	Reconstructing Point Sets from Distance Distributions. CoRR Shuai Huang, Ivan Dokmanic
2018	Misc	`conf`	Separake: Source Separation with a Little Help from Echoes. ICASSP Robin Scheibler, Diego Di Carlo, Antoine Deleforge, Ivan Dokmanic
2018	Misc	`conf`	Structure from Sound with Incomplete Data. ICASSP Miranda Krekovic, Gilles Baechler, Ivan Dokmanic, Martin Vetterli
2017	—	`conf`	Acoustic DoA Estimation by One Unsophisticated Sensor. LVA/ICA Dalia El Badawy, Ivan Dokmanic, Martin Vetterli
2017	J	`jnl`	Beyond Moore-Penrose Part I: Generalized Inverses that Minimize Matrix Norms. CoRR Ivan Dokmanic, Rémi Gribonval
2017	J	`jnl`	Beyond Moore-Penrose Part II: The Sparse Pseudoinverse. CoRR Ivan Dokmanic, Rémi Gribonval
2017	Misc	`conf`	FRIDA: FRI-based DOA estimation for arbitrary array layouts. ICASSP Hanjie Pan, Robin Scheibler, Eric Bezzam, Ivan Dokmanic, Martin Vetterli
2017	Misc	`conf`	Omnidirectional bats, point-to-plane distances, and the price of uniqueness. ICASSP Miranda Krekovic, Ivan Dokmanic, Martin Vetterli
2017	J	`jnl`	Pyroomacoustics: A Python package for audio room simulations and array processing algorithms. CoRR Robin Scheibler, Eric Bezzam, Ivan Dokmanic
2017	J	`jnl`	Separake: Source Separation with a Little Help From Echoes. CoRR Robin Scheibler, Diego Di Carlo, Antoine Deleforge, Ivan Dokmanic
2016	Misc	`conf`	Accurate recovery of a specularity from a few samples of the reflectance function. ICASSP Gilles Baechler, Ivan Dokmanic, Loïc Baboulaz, Martin Vetterli
2016	Misc	`conf`	EchoSLAM: Simultaneous localization and mapping with acoustic echoes. ICASSP Miranda Krekovic, Ivan Dokmanic, Martin Vetterli
2016	J	`jnl`	FRIDA: FRI-Based DOA Estimation for Arbitrary Array Layouts. CoRR Hanjie Pan, Robin Scheibler, Eric Bezzam, Ivan Dokmanic, Martin Vetterli
2016	Misc	`conf`	From acoustic room reconstruction to slam. ICASSP Ivan Dokmanic, Laurent Daudet, Martin Vetterli
2016	J	`jnl`	Inverse Problems with Invariant Multiscale Statistics. CoRR Ivan Dokmanic, Joan Bruna, Stéphane Mallat, Maarten V. de Hoop
2016	J	`jnl`	Look, no Beacons! Optimal All-in-One EchoSLAM. CoRR Miranda Krekovic, Ivan Dokmanic, Martin Vetterli
2016	J	`jnl`	Omnidirectional Bats, Point-to-Plane Distances, and the Price of Uniqueness. CoRR Miranda Krekovic, Ivan Dokmanic, Martin Vetterli
2016	J	`jnl`	Sampling Sparse Signals on the Sphere: Algorithms and Applications. IEEE Trans. Signal Process. Ivan Dokmanic, Yue M. Lu
2015	—	`ch.`	Anhören von Abständen und Hören von Formen: Inverse Probleme in Raumakustik und darüber hinaus. Ausgezeichnete Informatikdissertationen Ivan Dokmanic
2015	J	`jnl`	Euclidean Distance Matrices: A Short Walk Through Theory, Algorithms and Applications. CoRR Ivan Dokmanic, Reza Parhizkar, Juri Ranieri, Martin Vetterli
2015	J	`jnl`	Euclidean Distance Matrices: Essential theory, algorithms, and applications. IEEE Signal Process. Mag. Ivan Dokmanic, Reza Parhizkar, Juri Ranieri, Martin Vetterli
2015	—	`—`	Listening to Distances and Hearing Shapes - Inverse Problems in Room Acoustics and Beyond. Ivan Dokmanic
2015	Misc	`conf`	Raking echoes in the time domain. ICASSP Robin Scheibler, Ivan Dokmanic, Martin Vetterli
2015	J	`jnl`	Raking the Cocktail Party. IEEE J. Sel. Top. Signal Process. Ivan Dokmanic, Robin Scheibler, Martin Vetterli
2015	—	`conf`	Relax and unfold: Microphone localization with Euclidean distance matrices. EUSIPCO Ivan Dokmanic, Juri Ranieri, Martin Vetterli
2015	J	`jnl`	Sampling Sparse Signals on the Sphere: Algorithms and Applications. CoRR Ivan Dokmanic, Yue M. Lu
2015	Misc	`conf`	Sampling spherical finite rate of innovation signals. ICASSP Ivan Dokmanic, Yue M. Lu
2014	Misc	`conf`	Hardware and algorithms for ultrasonic depth imaging. ICASSP Ivan Dokmanic, Ivan J. Tashev
2014	—	`conf`	How to localize ten microphones in one finger snap. EUSIPCO Ivan Dokmanic, Laurent Daudet, Martin Vetterli
2014	J	`jnl`	Raking the Cocktail Party. CoRR Ivan Dokmanic, Robin Scheibler, Martin Vetterli
2014	Misc	`conf`	Single-channel indoor microphone localization. ICASSP Reza Parhizkar, Ivan Dokmanic, Martin Vetterli
2014	Misc	`conf`	Source localization and tracking in non-convex rooms. ICASSP Orhan Öçal, Ivan Dokmanic, Martin Vetterli
2013	Misc	`conf`	Beyond Moore-Penrose: Sparse pseudoinverse. ICASSP Ivan Dokmanic, Mihailo Kolundzija, Martin Vetterli
2013	Misc	`conf`	The Fukushima inverse problem. ICASSP Marta Martinez-Camara, Ivan Dokmanic, Juri Ranieri, Robin Scheibler, Martin Vetterli, Andreas Stohl
2012	Misc	`conf`	Room helps: Acoustic localization with finite elements. ICASSP Ivan Dokmanic, Martin Vetterli
2012	Misc	`conf`	Sampling and reconstruction of time-varying atmospheric emissions. ICASSP Juri Ranieri, Ivan Dokmanic, Amina Chebira, Martin Vetterli
2011	Misc	`conf`	Can one hear the shape of a room: The 2-D polygonal case. ICASSP Ivan Dokmanic, Yue M. Lu, Martin Vetterli
2011	—	`conf`	Sensor networks for diffusion fields: Detection of sources in space and time. Allerton Ivan Dokmanic, Juri Ranieri, Amina Chebira, Martin Vetterli
2010	J	`jnl`	Convolution on the n-sphere with application to PDF modeling. IEEE Trans. Signal Process. Ivan Dokmanic, Davor Petrinovic
2010	J	`jnl`	Efficient approximate scaling of spherical functions in the Fourier domain with generalization to hyperspheres. IEEE Trans. Signal Process. Ivan Dokmanic, Davor Petrinovic