On the Existence and Convergence of the Solution of PML Equations. - Matti Lassas; Erkki Somersalo (Computing, 1998)

Optimal Acoustic Measurements. - David Isaacson; Margaret Cheney; Matti Lassas (SIAM J. Appl. Math., 2001)

Wind velocity observation with a CW Doppler radar. - Matti Lassas; Mustapha Mataich; Samuli Siltanen; Erkki Somersalo (IEEE Trans. Geosci. Remote. Sens., 2002)

The Inverse Conductivity Problem with an Imperfectly Known Boundary. - Ville Kolehmainen; Matti Lassas; Petri Ola (SIAM J. Appl. Math., 2005)

Parallelized Bayesian inversion for three-dimensional dental X-ray imaging. - Ville Kolehmainen; Antti Vanne; Samuli Siltanen; Seppo Järvenpää; Jari P. Kaipio; Matti Lassas; Martti Kalke (IEEE Trans. Medical Imaging, 2006)

Wavelet-based reconstruction for limited-angle X-ray tomography. - Maaria Rantala; Simopekka Vänskä; Seppo Järvenpää; Martti Kalke; Matti Lassas; Jan Moberg; Samuli Siltanen (IEEE Trans. Medical Imaging, 2006)

Bayesian inversion method for 3D dental X-ray imaging. - Ville Kolehmainen; Antti Vanne; Samuli Siltanen; Seppo Järvenpää; Jari P. Kaipio; Matti Lassas; Martti Kalke (Elektrotech. Informationstechnik, 2007)

D-Bar Method for Electrical Impedance Tomography with Discontinuous Conductivities. - Kim Knudsen; Matti Lassas; Jennifer L. Mueller; Samuli Siltanen (SIAM J. Appl. Math., 2007)

The Inverse Conductivity Problem with an Imperfectly Known Boundary in Three Dimensions. - Ville Kolehmainen; Matti Lassas; Petri Ola (SIAM J. Appl. Math., 2007)

Limited Data X-Ray Tomography Using Nonlinear Evolution Equations. - Ville Kolehmainen; Matti Lassas; Samuli Siltanen (SIAM J. Sci. Comput., 2008)

Electrical Impedance Tomography Problem With Inaccurately Known Boundary and Contact Impedances. - Ville Kolehmainen; Matti Lassas; Petri Ola (IEEE Trans. Medical Imaging, 2008)

Focusing Waves in Unknown Media by Modified Time Reversal Iteration. - Matias F. Dahl; Anna Kirpichnikova; Matti Lassas (SIAM J. Control. Optim., 2009)

Cloaking Devices, Electromagnetic Wormholes, and Transformation Optics. - Allan Greenleaf; Yaroslav Kurylev; Matti Lassas; Gunther Uhlmann (SIAM Rev., 2009)

Infinite Photography: New Mathematical Model for High-Resolution Images. - Tapio Helin; Matti Lassas; Samuli Siltanen (J. Math. Imaging Vis., 2010)

Calderón's Inverse Problem with an Imperfectly Known Boundary and Reconstruction Up to a Conformal Deformation. - Ville Kolehmainen; Matti Lassas; Petri Ola (SIAM J. Math. Anal., 2010)

Determining Electrical and Heat Transfer Parameters Using Coupled Boundary Measurements. - Katsiaryna Krupchyk; Matti Lassas; Samuli Siltanen (SIAM J. Math. Anal., 2011)

Dynamic X-ray tomography with multiple sources. - Esa Niemi; Matti Lassas; Samuli Siltanen (ISPA, 2013)

Sparse Tomography. - Keijo Hämäläinen; Aki Kallonen; Ville Kolehmainen; Matti Lassas; Kati Niinimäki; Samuli Siltanen (SIAM J. Sci. Comput., 2013)

Reconstruction of a Conformally Euclidean Metric from Local Boundary Diffraction Travel Times. - Maarten V. de Hoop; Sean F. Holman; Einar Iversen; Matti Lassas; Bjørn Ursin (SIAM J. Math. Anal., 2014)

Dynamic multi-source X-ray tomography using a spacetime level set method. - Esa Niemi; Matti Lassas; Aki Kallonen; Lauri Harhanen; Keijo Hämäläinen; Samuli Siltanen (J. Comput. Phys., 2015)

Wave Phenomena. - Matti Lassas; Mikko Salo; Gunther Uhlmann (Handbook of Mathematical Methods in Imaging, 2015)

The Blow-up of Electromagnetic Fields in 3-Dimensional Invisibility Cloaking for Maxwell's Equations. - Matti Lassas; Ting Zhou (SIAM J. Appl. Math., 2016)

Multiresolution Parameter Choice Method for Total Variation Regularized Tomography. - Kati Niinimäki; Matti Lassas; Keijo Hämäläinen; Aki Kallonen; Ville Kolehmainen; Esa Niemi; Samuli Siltanen (SIAM J. Imaging Sci., 2016)

Amplitude noise suppression and orthogonal multiplexing using injection-locked single-mode VCSEL. - Vladimir S. Lyubopytov; Tuomo von Lerber; Matti Lassas; Mohammadreza Malekizandi; Arkadi Chipouline; Franko Küppers (OFC, 2017)

Optical computing by injection-locked lasers. - Tuomo von Lerber; Matti Lassas; Quang Trung Le; Vladimir Lyubopytov; Arkadi Chipouline; Klaus Hofmann; Franko Küppers (CoRR, 2017)

Fitting a Putative Manifold to Noisy Data. - Charles Fefferman; Sergei Ivanov 001; Yaroslav Kurylev; Matti Lassas; Hariharan Narayanan (COLT, 2018)

Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography. - Tatiana A. Bubba; Gitta Kutyniok; Matti Lassas; Maximilian März; Wojciech Samek; Samuli Siltanen; Vignesh Srinivasan (CoRR, 2018)

Superdimensional Metamaterial Resonators From Sub-Riemannian Geometry. - Allan Greenleaf; Henrik Kettunen; Yaroslav Kurylev; Matti Lassas; Gunther Uhlmann (SIAM J. Appl. Math., 2018)

On Absence and Existence of the Anomalous Localized Resonance without the Quasi-static Approximation. - Henrik Kettunen; Matti Lassas; Petri Ola (SIAM J. Appl. Math., 2018)

Deep learning architectures for nonlinear operator functions and nonlinear inverse problems. - Maarten V. de Hoop; Matti Lassas; Christopher A. Wong (CoRR, 2019)

Reconstruction and Interpolation of Manifolds. I: The Geometric Whitney Problem. - Charles Fefferman; Sergei Ivanov 001; Yaroslav Kurylev; Matti Lassas; Hariharan Narayanan (Found. Comput. Math., 2020)

Reconstruction of a Riemannian Manifold from Noisy Intrinsic Distances. - Charles Fefferman; Sergei Ivanov 001; Matti Lassas; Hariharan Narayanan (SIAM J. Math. Data Sci., 2020)

Learning the optimal Tikhonov regularizer for inverse problems. - Giovanni S. Alberti; Ernesto De Vito; Matti Lassas; Luca Ratti; Matteo Santacesaria (NeurIPS, 2021)

Learning the optimal regularizer for inverse problems. - Giovanni S. Alberti; Ernesto De Vito; Matti Lassas; Luca Ratti; Matteo Santacesaria (CoRR, 2021)

Material-separating regularizer for multi-energy X-ray tomography. - Jacek Gondzio; Matti Lassas; Salla-Maaria Latva-Äijö; Samuli Siltanen; Filippo Zanetti (CoRR, 2021)

Construction of Artificial Point Sources for a Linear Wave Equation in Unknown Medium. - Anna Kirpichnikova; Jussi Korpela; Matti Lassas; Lauri Oksanen (SIAM J. Control. Optim., 2021)

Simultaneous Reconstruction of Conductivity, Boundary Shape, and Contact Impedances in Electrical Impedance Tomography. - Juan P. Agnelli; Ville Kolehmainen; Matti Lassas; Petri Ola; Samuli Siltanen (SIAM J. Imaging Sci., 2021)

Deep Neural Networks for Inverse Problems with Pseudodifferential Operators: An Application to Limited-Angle Tomography. - Tatiana A. Bubba; Mathilde Galinier; Matti Lassas; Marco Prato; Luca Ratti; Samuli Siltanen (SIAM J. Imaging Sci., 2021)

Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows. - Michael Puthawala; Matti Lassas; Ivan Dokmanic; Maarten V. de Hoop (ICML, 2022)

An inverse problem for a semi-linear wave equation: a numerical study. - Matti Lassas; Tony Liimatainen; Leyter Potenciano-Machado; Teemu Tyni (CoRR, 2022)

Deep Invertible Approximation of Topologically Rich Maps between Manifolds. - Michael Puthawala; Matti Lassas; Ivan Dokmanic; Pekka Pankka; Maarten V. de Hoop (CoRR, 2022)

Globally Injective ReLU Networks. - Michael Puthawala; Konik Kothari; Matti Lassas; Ivan Dokmanic; Maarten V. de Hoop (J. Mach. Learn. Res., 2022)

Analysis of a Dynamical System Modeling Lasers and Applications for Optical Neural Networks. - Lauri Ylinen; Tuomo von Lerber; Franko Küppers; Matti Lassas (SIAM J. Appl. Dyn. Syst., 2022)

Invisibility Cloaking and Transformation Optics for Three Dimensional Manifolds and Applications in Cosmology. - Tracey Balehowsky; Matti Lassas; Pekka Pankka; Ville Sirviö (SIAM J. Math. Anal., 2022)

Globally injective and bijective neural operators. - Takashi Furuya; Michael Puthawala; Matti Lassas; Maarten V. de Hoop (NeurIPS, 2023)

A Transfer Principle: Universal Approximators Between Metric Spaces From Euclidean Universal Approximators. - Anastasis Kratsios; Chong Liu; Matti Lassas; Maarten V. de Hoop; Ivan Dokmanic (CoRR, 2023)

Quantum computing algorithms for inverse problems on graphs and an NP-complete inverse problem. - Joonas Ilmavirta; Matti Lassas; Jinpeng Lu; Lauri Oksanen; Lauri Ylinen (CoRR, 2023)

Inverse Problems for Discrete Heat Equations and Random Walks for a Class of Graphs. - Emilia L. K. Blåsten; Hiroshi Isozaki; Matti Lassas; Jinpeng Lu (SIAM J. Discret. Math., 2023)

Can neural operators always be continuously discretized? - Takashi Furuya; Michael Puthawala; Matti Lassas; Maarten V. de Hoop (NeurIPS, 2024)

Mixture of Experts Soften the Curse of Dimensionality in Operator Learning. - Anastasis Kratsios; Takashi Furuya; Jose Antonio Lara Benitez; Matti Lassas; Maarten V. de Hoop (CoRR, 2024)

Reducing the cost of posterior sampling in linear inverse problems via task-dependent score learning. - Fabian Schneider; Duc-Lam Duong; Matti Lassas; Maarten V. de Hoop; Tapio Helin (CoRR, 2024)

Learning sparsity-promoting regularizers for linear inverse problems. - Giovanni S. Alberti; Ernesto De Vito; Tapio Helin; Matti Lassas; Luca Ratti; Matteo Santacesaria (CoRR, 2024)

TILT: Topological Interface Recovery in Limited-Angle Tomography. - Elli Karvonen; Matti Lassas; Pekka Pankka; Samuli Siltanen (SIAM J. Imaging Sci., 2024)

Disjoint Data Inverse Problem on Manifolds with Quantum Chaos Bounds. - Matti Lassas; Medet Nursultanov; Lauri Oksanen; Lauri Ylinen (SIAM J. Math. Anal., 2024)

Semialgebraic Neural Networks: From roots to representations. - S. David Mis; Matti Lassas; Maarten V. de Hoop (ICLR, 2025)

On the Lack of External Response of a Nonlinear Medium in the Second-Harmonic Generation Process. - Fioralba Cakoni; Narek Hovsepyan; Matti Lassas; Michael Vogelius (SIAM J. Math. Anal., 2025)

Stroke classification using Virtual Hybrid Edge Detection from in silico electrical impedance tomography data. - Juan P. Agnelli; Fernando Silva de Moura; Siiri Rautio; Melody Alsaker; Rashmi Murthy; Matti Lassas; Samuli Siltanen (CoRR, 2025)