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2020 – today
- 2024
[j23]Sidharth Gupta
, Konik Kothari, Valentin Debarnot, Ivan Dokmanic:
Differentiable Uncalibrated Imaging. IEEE Trans. Computational Imaging 10: 1-16 (2024)- [j22]Tianlin Liu, Jose Antonio Lara Benitez, Florian Faucher, AmirEhsan Khorashadizadeh, Maarten V. de Hoop, Ivan Dokmanic:
WaveBench: Benchmarking Data-driven Solvers for Linear Wave Propagation PDEs. Trans. Mach. Learn. Res. 2024 (2024) - [c45]Liming Pan, Cheng Shi, Ivan Dokmanic:
A Graph Dynamics Prior for Relational Inference. AAAI 2024: 14508-14516 - [i52]AmirEhsan Khorashadizadeh, Valentin Debarnot, Tianlin Liu, Ivan Dokmanic:
GLIMPSE: Generalized Local Imaging with MLPs. CoRR abs/2401.00816 (2024) - [i51]Cheng Shi, Liming Pan, Ivan Dokmanic:
A spring-block theory of feature learning in deep neural networks. CoRR abs/2407.19353 (2024) - [i50]Jonas Linkerhägner, Cheng Shi, Ivan Dokmanic:
Joint Graph Rewiring and Feature Denoising via Spectral Resonance. CoRR abs/2408.07191 (2024) - 2023
- [j21]Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanic:
Small Transformers Compute Universal Metric Embeddings. J. Mach. Learn. Res. 24: 170:1-170:48 (2023) - [j20]Shuai Huang, Mona Zehni, Ivan Dokmanic, Zhizhen Zhao:
Orthogonal Matrix Retrieval with Spatial Consensus for 3D Unknown View Tomography. SIAM J. Imaging Sci. 16(3): 1398-1439 (2023) - [j19]AmirEhsan Khorashadizadeh, Konik Kothari, Leonardo Salsi, Ali Aghababaei Harandi, Maarten V. de Hoop, Ivan Dokmanic:
Conditional Injective Flows for Bayesian Imaging. IEEE Trans. Computational Imaging 9: 224-237 (2023) - [j18]Dalia El Badawy, Viktor Larsson, Marc Pollefeys, Ivan Dokmanic:
Localizing Unsynchronized Sensors With Unknown Sources. IEEE Trans. Signal Process. 71: 641-654 (2023) - [c44]Valentin Debarnot, Sidharth Gupta, Konik Kothari, Ivan Dokmanic:
Joint Cryo-ET Alignment and Reconstruction with Neural Deformation Fields. ICASSP 2023: 1-5 - [c43]AmirEhsan Khorashadizadeh, Anadi Chaman, Valentin Debarnot, Ivan Dokmanic:
FunkNN: Neural Interpolation for Functional Generation. ICLR 2023 - [c42]Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, Ivan Dokmanic, David Belius:
A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression. NeurIPS 2023 - [i49]AmirEhsan Khorashadizadeh, Sepehr Eskandari, Vahid Khorashadi-Zadeh, Ivan Dokmanic:
Deep Injective Prior for Inverse Scattering. CoRR abs/2301.03092 (2023) - [i48]Antoine Maillard, Afonso S. Bandeira, David Belius, Ivan Dokmanic, Shuta Nakajima:
Injectivity of ReLU networks: perspectives from statistical physics. CoRR abs/2302.14112 (2023) - [i47]Anastasis Kratsios, Chong Liu, Matti Lassas, Maarten V. de Hoop, Ivan Dokmanic:
A Transfer Principle: Universal Approximators Between Metric Spaces From Euclidean Universal Approximators. CoRR abs/2304.12231 (2023) - [i46]Liming Pan, Cheng Shi, Ivan Dokmanic:
A Dynamical Graph Prior for Relational Inference. CoRR abs/2306.06041 (2023) - [i45]Cheng Shi, Maarten V. de Hoop, Ivan Dokmanic:
Harpa: High-Rate Phase Association with Travel Time Neural Fields. CoRR abs/2307.07572 (2023) - [i44]Tin Sum Cheng, Aurélien Lucchi, Ivan Dokmanic, Anastasis Kratsios, David Belius:
A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression. CoRR abs/2310.00987 (2023) - 2022
- [j17]Michael Puthawala, Konik Kothari, Matti Lassas, Ivan Dokmanic, Maarten V. de Hoop:
Globally Injective ReLU Networks. J. Mach. Learn. Res. 23: 105:1-105:55 (2022) - [j16]Benjamín Béjar Haro, Ivan Dokmanic, René Vidal:
The Fastest $\ell _{1, \infty }$ℓ1, ∞ Prox in the West. IEEE Trans. Pattern Anal. Mach. Intell. 44(7): 3858-3869 (2022) - [j15]Tianlin Liu, Anadi Chaman, David Belius, Ivan Dokmanic:
Learning Multiscale Convolutional Dictionaries for Image Reconstruction. IEEE Trans. Computational Imaging 8: 425-437 (2022) - [j14]Sidharth Gupta, Ivan Dokmanic:
Total Least Squares Phase Retrieval. IEEE Trans. Signal Process. 70: 536-549 (2022) - [c41]Tin Vlasic, Hieu Nguyen, AmirEhsan Khorashadizadeh, Ivan Dokmanic:
Implicit Neural Representation for Mesh-Free Inverse Obstacle Scattering. IEEECONF 2022: 947-952 - [c40]Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, Ivan Dokmanic:
Universal Approximation Under Constraints is Possible with Transformers. ICLR 2022 - [c39]Liming Pan, Cheng Shi, Ivan Dokmanic:
Neural Link Prediction with Walk Pooling. ICLR 2022 - [c38]Michael Puthawala, Matti Lassas, Ivan Dokmanic, Maarten V. de Hoop:
Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows. ICML 2022: 17959-17983 - [i43]AmirEhsan Khorashadizadeh, Konik Kothari, Leonardo Salsi, Ali Aghababaei Harandi, Maarten V. de Hoop, Ivan Dokmanic:
Conditional Injective Flows for Bayesian Imaging. CoRR abs/2204.07664 (2022) - [i42]Tin Vlasic, Hieu Nguyen, Ivan Dokmanic:
Implicit Neural Representation for Mesh-Free Inverse Obstacle Scattering. CoRR abs/2206.02027 (2022) - [i41]Shuai Huang, Mona Zehni, Ivan Dokmanic, Zhizhen Zhao:
Orthogonal Matrix Retrieval with Spatial Consensus for 3D Unknown-View Tomography. CoRR abs/2207.02985 (2022) - [i40]Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanic:
Small Transformers Compute Universal Metric Embeddings. CoRR abs/2209.06788 (2022) - [i39]Michael Puthawala, Matti Lassas, Ivan Dokmanic, Pekka Pankka, Maarten V. de Hoop:
Deep Invertible Approximation of Topologically Rich Maps between Manifolds. CoRR abs/2210.00577 (2022) - [i38]Sidharth Gupta, Konik Kothari, Valentin Debarnot, Ivan Dokmanic:
Differentiable Uncalibrated Imaging. CoRR abs/2211.10525 (2022) - [i37]AmirEhsan Khorashadizadeh, Ali Aghababaei Harandi, Tin Vlasic, Hieu Nguyen, Ivan Dokmanic:
Deep Variational Inverse Scattering. CoRR abs/2212.04309 (2022) - [i36]Cheng Shi, Liming Pan, Hong Hu, Ivan Dokmanic:
Statistical Mechanics of Generalization In Graph Convolution Networks. CoRR abs/2212.13069 (2022) - [i35]AmirEhsan Khorashadizadeh, Anadi Chaman, Valentin Debarnot, Ivan Dokmanic:
FunkNN: Neural Interpolation for Functional Generation. CoRR abs/2212.14042 (2022) - 2021
- [j13]Puoya Tabaghi, Ivan Dokmanic:
On Procrustes Analysis in Hyperbolic Space. IEEE Signal Process. Lett. 28: 1120-1124 (2021) - [j12]Shuai Huang, Ivan Dokmanic:
Reconstructing Point Sets From Distance Distributions. IEEE Trans. Signal Process. 69: 1811-1827 (2021) - [c37]Anadi Chaman, Ivan Dokmanic:
Truly Shift-Equivariant Convolutional Neural Networks with Adaptive Polyphase Upsampling. ACSCC 2021: 1113-1120 - [c36]Anadi Chaman, Ivan Dokmanic:
Truly Shift-Invariant Convolutional Neural Networks. CVPR 2021: 3773-3783 - [c35]Konik Kothari, AmirEhsan Khorashadizadeh, Maarten V. de Hoop, Ivan Dokmanic:
Trumpets: Injective flows for inference and inverse problems. UAI 2021: 1269-1278 - [i34]Konik Kothari, AmirEhsan Khorashadizadeh, Maarten V. de Hoop, Ivan Dokmanic:
Trumpets: Injective Flows for Inference and Inverse Problems. CoRR abs/2102.10461 (2021) - [i33]Anadi Chaman, Ivan Dokmanic:
Truly shift-equivariant convolutional neural networks with adaptive polyphase upsampling. CoRR abs/2105.04040 (2021) - [i32]Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, Ivan Dokmanic:
Universal Approximation Under Constraints is Possible with Transformers. CoRR abs/2110.03303 (2021) - [i31]Michael Puthawala, Matti Lassas, Ivan Dokmanic, Maarten V. de Hoop:
Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows. CoRR abs/2110.04227 (2021) - [i30]Liming Pan, Cheng Shi, Ivan Dokmanic:
Neural Link Prediction with Walk Pooling. CoRR abs/2110.04375 (2021) - 2020
- [j11]Puoya Tabaghi, Ivan Dokmanic, Martin Vetterli:
Kinetic Euclidean Distance Matrices. IEEE Trans. Signal Process. 68: 452-465 (2020) - [j10]Miranda Krekovic, Ivan Dokmanic, Martin Vetterli:
Shapes From Echoes: Uniqueness From Point-to-Plane Distance Matrices. IEEE Trans. Signal Process. 68: 2480-2498 (2020) - [j9]Shuai Huang, Sidharth Gupta, Ivan Dokmanic:
Solving Complex Quadratic Systems With Full-Rank Random Matrices. IEEE Trans. Signal Process. 68: 4782-4796 (2020) - [c34]Mona Zehni, Shuai Huang, Ivan Dokmanic, Zhizhen Zhao:
3D Unknown View Tomography Via Rotation Invariants. ICASSP 2020: 1449-1453 - [c33]Sidharth Gupta, Rémi Gribonval, Laurent Daudet, Ivan Dokmanic:
Fast Optical System Identification by Numerical Interferometry. ICASSP 2020: 1474-1478 - [c32]Puoya Tabaghi, Ivan Dokmanic:
Hyperbolic Distance Matrices. KDD 2020: 1728-1738 - [c31]Konik Kothari, Maarten V. de Hoop, Ivan Dokmanic:
Learning the Geometry of Wave-Based Imaging. NeurIPS 2020 - [i29]Puoya Tabaghi, Ivan Dokmanic:
Hyperbolic Distance Matrices. CoRR abs/2005.08672 (2020) - [i28]Konik Kothari, Maarten V. de Hoop, Ivan Dokmanic:
Learning the geometry of wave-based imaging. CoRR abs/2006.05854 (2020) - [i27]Michael Puthawala, Konik Kothari, Matti Lassas, Ivan Dokmanic, Maarten V. de Hoop:
Globally Injective ReLU Networks. CoRR abs/2006.08464 (2020) - [i26]Puoya Tabaghi, Ivan Dokmanic:
Geometry of Comparisons. CoRR abs/2006.09858 (2020) - [i25]Tianlin Liu, Anadi Chaman, David Belius, Ivan Dokmanic:
Interpreting U-Nets via Task-Driven Multiscale Dictionary Learning. CoRR abs/2011.12815 (2020) - [i24]Anadi Chaman, Ivan Dokmanic:
Truly shift-invariant convolutional neural networks. CoRR abs/2011.14214 (2020)
2010 – 2019
- 2019
- [j8]Ivan Dokmanic, Rémi Gribonval:
Concentration of the Frobenius Norm of Generalized Matrix Inverses. SIAM J. Matrix Anal. Appl. 40(1): 92-121 (2019) - [j7]Ivan Dokmanic:
Permutations Unlabeled Beyond Sampling Unknown. IEEE Signal Process. Lett. 26(6): 823-827 (2019) - [c30]Mona Zehni, Shuai Huang, Ivan Dokmanic, Zhizhen Zhao:
Distance retrieval from unknown view tomography of 2D point sources. Computational Imaging 2019 - [c29]Anadi Chaman, Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanic:
Multipath-enabled Private Audio with Noise. ICASSP 2019: 685-689 - [c28]Puoya Tabaghi, Ivan Dokmanic, Martin Vetterli:
On the Move: Localization with Kinetic Euclidean Distance Matrices. ICASSP 2019: 4893-4897 - [c27]Mona Zehni, Shuai Huang, Ivan Dokmanic, Zhizhen Zhao:
Geometric Invariants for Sparse Unknown View Tomography. ICASSP 2019: 5027-5031 - [c26]Shuai Huang, Sidharth Gupta, Ivan Dokmanic:
Solving Complex Quadratic Equations with Full-rank Random Gaussian Matrices. ICASSP 2019: 5596-5600 - [c25]Konik Kothari, Sidharth Gupta, Maarten V. de Hoop, Ivan Dokmanic:
Random mesh projectors for inverse problems. ICLR (Poster) 2019 - [c24]Sidharth Gupta, Rémi Gribonval, Laurent Daudet, Ivan Dokmanic:
Don't take it lightly: Phasing optical random projections with unknown operators. NeurIPS 2019: 14826-14836 - [i23]Puoya Tabaghi, Maarten V. de Hoop, Ivan Dokmanic:
Learning Schatten-Von Neumann Operators. CoRR abs/1901.10076 (2019) - [i22]Shuai Huang, Sidharth Gupta, Ivan Dokmanic:
Solving Complex Quadratic Systems with Full-Rank Random Matrices. CoRR abs/1902.05612 (2019) - [i21]Miranda Krekovic, Ivan Dokmanic, Martin Vetterli:
Shapes from Echoes: Uniqueness from Point-to-Plane Distance Matrices. CoRR abs/1902.09959 (2019) - [i20]Sidharth Gupta, Rémi Gribonval, Laurent Daudet, Ivan Dokmanic:
Don't take it lightly: Phasing optical random projections with unknown operators. CoRR abs/1907.01703 (2019) - [i19]Benjamín Béjar Haro, Ivan Dokmanic, René Vidal:
The fastest 𝓁1, ∞ prox in the west. CoRR abs/1910.03749 (2019) - 2018
- [j6]Dalia El Badawy, Ivan Dokmanic:
Direction of Arrival With One Microphone, a Few LEGOs, and Non-Negative Matrix Factorization. IEEE ACM Trans. Audio Speech Lang. Process. 26(12): 2436-2446 (2018) - [c23]Robin Scheibler, Eric Bezzam, Ivan Dokmanic:
Pyroomacoustics: A Python Package for Audio Room Simulation and Array Processing Algorithms. ICASSP 2018: 351-355 - [c22]Miranda Krekovic, Gilles Baechler, Ivan Dokmanic, Martin Vetterli:
Structure from Sound with Incomplete Data. ICASSP 2018: 3539-3543 - [c21]Robin Scheibler, Diego Di Carlo, Antoine Deleforge, Ivan Dokmanic:
Separake: Source Separation with a Little Help from Echoes. ICASSP 2018: 6897-6901 - [c20]Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanic:
Cocktails, but no Party: Multipath-Enabled Private Audio. IWAENC 2018: 186-190 - [i18]Dalia El Badawy, Ivan Dokmanic:
Direction of Arrival with One Microphone, a few LEGOs, and Non-Negative Matrix Factorization. CoRR abs/1801.03740 (2018) - [i17]Shuai Huang, Ivan Dokmanic:
Reconstructing Point Sets from Distance Distributions. CoRR abs/1804.02465 (2018) - [i16]Sidharth Gupta, Konik Kothari, Maarten V. de Hoop, Ivan Dokmanic:
Deep Mesh Projectors for Inverse Problems. CoRR abs/1805.11718 (2018) - [i15]Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanic:
Cocktails, but no party: multipath-enabled private audio. CoRR abs/1809.05862 (2018) - [i14]Ivan Dokmanic, Rémi Gribonval:
Concentration of the Frobenius norms of pseudoinverses. CoRR abs/1810.07921 (2018) - [i13]Anadi Chaman, Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanic:
Multipath-enabled private audio with noise. CoRR abs/1811.07065 (2018) - [i12]Ivan Dokmanic:
Permutations Unlabeled beyond Sampling Unknown. CoRR abs/1812.00498 (2018) - 2017
- [c19]Dalia El Badawy, Ivan Dokmanic, Martin Vetterli:
Acoustic DoA Estimation by One Unsophisticated Sensor. LVA/ICA 2017: 89-98 - [c18]Hanjie Pan, Robin Scheibler, Eric Bezzam, Ivan Dokmanic, Martin Vetterli:
FRIDA: FRI-based DOA estimation for arbitrary array layouts. ICASSP 2017: 3186-3190 - [c17]Miranda Krekovic, Ivan Dokmanic, Martin Vetterli:
Omnidirectional bats, point-to-plane distances, and the price of uniqueness. ICASSP 2017: 3261-3265 - [i11]Ivan Dokmanic, Rémi Gribonval:
Beyond Moore-Penrose Part I: Generalized Inverses that Minimize Matrix Norms. CoRR abs/1706.08349 (2017) - [i10]Ivan Dokmanic, Rémi Gribonval:
Beyond Moore-Penrose Part II: The Sparse Pseudoinverse. CoRR abs/1706.08701 (2017) - [i9]Robin Scheibler, Eric Bezzam, Ivan Dokmanic:
Pyroomacoustics: A Python package for audio room simulations and array processing algorithms. CoRR abs/1710.04196 (2017) - [i8]Robin Scheibler, Diego Di Carlo, Antoine Deleforge, Ivan Dokmanic:
Separake: Source Separation with a Little Help From Echoes. CoRR abs/1711.06805 (2017) - 2016
- [j5]Ivan Dokmanic, Yue M. Lu:
Sampling Sparse Signals on the Sphere: Algorithms and Applications. IEEE Trans. Signal Process. 64(1): 189-202 (2016) - [c16]Miranda Krekovic, Ivan Dokmanic, Martin Vetterli:
EchoSLAM: Simultaneous localization and mapping with acoustic echoes. ICASSP 2016: 11-15 - [c15]Gilles Baechler, Ivan Dokmanic, Loïc Baboulaz, Martin Vetterli:
Accurate recovery of a specularity from a few samples of the reflectance function. ICASSP 2016: 1596-1600 - [c14]Ivan Dokmanic, Laurent Daudet, Martin Vetterli:
From acoustic room reconstruction to slam. ICASSP 2016: 6345-6349 - [i7]Miranda Krekovic, Ivan Dokmanic, Martin Vetterli:
Look, no Beacons! Optimal All-in-One EchoSLAM. CoRR abs/1608.08753 (2016) - [i6]Ivan Dokmanic, Joan Bruna, Stéphane Mallat, Maarten V. de Hoop:
Inverse Problems with Invariant Multiscale Statistics. CoRR abs/1609.05502 (2016) - [i5]Miranda Krekovic, Ivan Dokmanic, Martin Vetterli:
Omnidirectional Bats, Point-to-Plane Distances, and the Price of Uniqueness. CoRR abs/1609.05512 (2016) - [i4]Hanjie Pan, Robin Scheibler, Eric Bezzam, Ivan Dokmanic, Martin Vetterli:
FRIDA: FRI-Based DOA Estimation for Arbitrary Array Layouts. CoRR abs/1612.00876 (2016) - 2015
- [b1]Ivan Dokmanic:
Listening to Distances and Hearing Shapes - Inverse Problems in Room Acoustics and Beyond. EPFL, Switzerland, 2015 - [j4]Ivan Dokmanic, Robin Scheibler, Martin Vetterli:
Raking the Cocktail Party. IEEE J. Sel. Top. Signal Process. 9(5): 825-836 (2015) - [j3]Ivan Dokmanic, Reza Parhizkar, Juri Ranieri, Martin Vetterli:
Euclidean Distance Matrices: Essential theory, algorithms, and applications. IEEE Signal Process. Mag. 32(6): 12-30 (2015) - [c13]Ivan Dokmanic, Juri Ranieri, Martin Vetterli:
Relax and unfold: Microphone localization with Euclidean distance matrices. EUSIPCO 2015: 265-269 - [c12]Robin Scheibler, Ivan Dokmanic, Martin Vetterli:
Raking echoes in the time domain. ICASSP 2015: 554-558 - [c11]Ivan Dokmanic, Yue M. Lu:
Sampling spherical finite rate of innovation signals. ICASSP 2015: 5962-5966 - [p1]Ivan Dokmanic:
Anhören von Abständen und Hören von Formen: Inverse Probleme in Raumakustik und darüber hinaus. Ausgezeichnete Informatikdissertationen 2015: 81-90 - [i3]Ivan Dokmanic, Reza Parhizkar, Juri Ranieri, Martin Vetterli:
Euclidean Distance Matrices: A Short Walk Through Theory, Algorithms and Applications. CoRR abs/1502.07541 (2015) - [i2]Ivan Dokmanic, Yue M. Lu:
Sampling Sparse Signals on the Sphere: Algorithms and Applications. CoRR abs/1502.07577 (2015) - 2014
- [c10]Ivan Dokmanic, Laurent Daudet, Martin Vetterli:
How to localize ten microphones in one finger snap. EUSIPCO 2014: 2275-2279 - [c9]Orhan Öçal, Ivan Dokmanic, Martin Vetterli:
Source localization and tracking in non-convex rooms. ICASSP 2014: 1429-1433 - [c8]Reza Parhizkar, Ivan Dokmanic, Martin Vetterli:
Single-channel indoor microphone localization. ICASSP 2014: 1434-1438 - [c7]Ivan Dokmanic, Ivan J. Tashev:
Hardware and algorithms for ultrasonic depth imaging. ICASSP 2014: 6702-6706 - [i1]Ivan Dokmanic, Robin Scheibler, Martin Vetterli:
Raking the Cocktail Party. CoRR abs/1407.5514 (2014) - 2013
- [c6]Marta Martinez-Camara, Ivan Dokmanic, Juri Ranieri, Robin Scheibler, Martin Vetterli, Andreas Stohl:
The Fukushima inverse problem. ICASSP 2013: 4330-4334 - [c5]Ivan Dokmanic, Mihailo Kolundzija, Martin Vetterli:
Beyond Moore-Penrose: Sparse pseudoinverse. ICASSP 2013: 6526-6530 - 2012
- [c4]Ivan Dokmanic, Martin Vetterli:
Room helps: Acoustic localization with finite elements. ICASSP 2012: 2617-2620 - [c3]Juri Ranieri, Ivan Dokmanic, Amina Chebira, Martin Vetterli:
Sampling and reconstruction of time-varying atmospheric emissions. ICASSP 2012: 3673-3676 - 2011
- [c2]Ivan Dokmanic, Juri Ranieri, Amina Chebira, Martin Vetterli:
Sensor networks for diffusion fields: Detection of sources in space and time. Allerton 2011: 1552-1558 - [c1]Ivan Dokmanic, Yue M. Lu, Martin Vetterli:
Can one hear the shape of a room: The 2-D polygonal case. ICASSP 2011: 321-324 - 2010
- [j2]Ivan Dokmanic, Davor Petrinovic:
Convolution on the n-sphere with application to PDF modeling. IEEE Trans. Signal Process. 58(3): 1157-1170 (2010) - [j1]Ivan Dokmanic, Davor Petrinovic:
Efficient approximate scaling of spherical functions in the Fourier domain with generalization to hyperspheres. IEEE Trans. Signal Process. 58(11): 5909-5914 (2010)
Coauthor Index
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