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Stéphane Mallat
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2020 – today
- 2024
- [c49]Zahra Kadkhodaie, Florentin Guth, Eero P. Simoncelli, Stéphane Mallat:
Generalization in diffusion models arises from geometry-adaptive harmonic representations. ICLR 2024 - [i43]Etienne Lempereur, Stéphane Mallat:
Hierarchic Flows to Estimate and Sample High-dimensional Probabilities. CoRR abs/2405.03468 (2024) - 2023
- [c48]Zahra Kadkhodaie, Florentin Guth, Stéphane Mallat, Eero P. Simoncelli
:
Learning multi-scale local conditional probability models of images. ICLR 2023 - [c47]Florentin Guth, Etienne Lempereur, Joan Bruna, Stéphane Mallat:
Conditionally Strongly Log-Concave Generative Models. ICML 2023: 12224-12251 - [i42]Zahra Kadkhodaie, Florentin Guth, Stéphane Mallat, Eero P. Simoncelli:
Learning multi-scale local conditional probability models of images. CoRR abs/2303.02984 (2023) - [i41]Florentin Guth, Brice Ménard
A Rainbow in Deep Network Black Boxes. CoRR abs/2305.18512 (2023) - [i40]Florentin Guth, Etienne Lempereur, Joan Bruna, Stéphane Mallat:
Conditionally Strongly Log-Concave Generative Models. CoRR abs/2306.00181 (2023) - [i39]Sihao Cheng
Scattering Spectra Models for Physics. CoRR abs/2306.17210 (2023) - [i38]Zahra Kadkhodaie, Florentin Guth, Eero P. Simoncelli
Generalization in diffusion models arises from geometry-adaptive harmonic representation. CoRR abs/2310.02557 (2023) - 2022
- [j32]Antoine Brochard
Particle gradient descent model for point process generation. Stat. Comput. 32(3): 49 (2022) - [c46]Antoine Brochard, Sixin Zhang, Stéphane Mallat:
Generalized rectifier wavelet covariance models for texture synthesis. ICLR 2022 - [c45]Florentin Guth, John Zarka, Stéphane Mallat:
Phase Collapse in Neural Networks. ICLR 2022 - [c44]Florentin Guth, Simon Coste, Valentin De Bortoli, Stéphane Mallat:
Wavelet Score-Based Generative Modeling. NeurIPS 2022 - [i37]Antoine Brochard, Sixin Zhang, Stéphane Mallat:
Generalized Rectifier Wavelet Covariance Models For Texture Synthesis. CoRR abs/2203.07902 (2022) - [i36]Rudy Morel, Gaspar Rochette, Roberto Leonarduzzi, Jean-Philippe Bouchaud, Stéphane Mallat:
Scale Dependencies and Self-Similarity Through Wavelet Scattering Covariance. CoRR abs/2204.10177 (2022) - [i35]Tanguy Marchand, Misaki Ozawa, Giulio Biroli, Stéphane Mallat:
Wavelet Conditional Renormalization Group. CoRR abs/2207.04941 (2022) - [i34]Florentin Guth, Simon Coste, Valentin De Bortoli, Stéphane Mallat:
Wavelet Score-Based Generative Modeling. CoRR abs/2208.05003 (2022) - 2021
- [c43]John Zarka, Florentin Guth, Stéphane Mallat:
Separation and Concentration in Deep Networks. ICLR 2021 - [i33]Florentin Guth, John Zarka, Stéphane Mallat:
Phase Collapse in Neural Networks. CoRR abs/2110.05283 (2021) - 2020
- [j31]Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Muawiz Chaudhary, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine-Emanuele Cella, Michael Eickenberg:
Kymatio: Scattering Transforms in Python. J. Mach. Learn. Res. 21: 60:1-60:6 (2020) - [c42]John Zarka, Louis Thiry, Tomás Angles, Stéphane Mallat:
Deep Network Classification by Scattering and Homotopy Dictionary Learning. ICLR 2020 - [i32]Antoine Brochard, Bartlomiej Blaszczyszyn, Stéphane Mallat, Sixin Zhang:
Particle gradient descent model for point process generation. CoRR abs/2010.14928 (2020) - [i31]John Zarka, Florentin Guth, Stéphane Mallat:
Separation and Concentration in Deep Networks. CoRR abs/2012.10424 (2020)
2010 – 2019
- 2019
- [j30]Joakim Andén
Joint Time-Frequency Scattering. IEEE Trans. Signal Process. 67(14): 3704-3718 (2019) - [c41]Roberto Leonarduzzi, Gaspar Rochette, Jean-Phillipe Bouchaud, Stéphane Mallat:
Maximum-entropy Scattering Models for Financial Time Series. ICASSP 2019: 5496-5500 - [c40]Antoine Brochard, Bartlomiej Blaszczyszyn, Stéphane Mallat, Sixin Zhang:
Statistical learning of geometric characteristics of wireless networks. INFOCOM 2019: 2224-2232 - [i30]John Zarka, Louis Thiry
Deep Network classification by Scattering and Homotopy dictionary learning. CoRR abs/1910.03561 (2019) - [i29]Sixin Zhang, Stéphane Mallat:
Maximum Entropy Models from Phase Harmonic Covariances. CoRR abs/1911.10017 (2019) - 2018
- [c39]Tomás Angles, Stéphane Mallat:
Generative networks as inverse problems with Scattering transforms. ICLR (Poster) 2018 - [c38]Mathieu Andreux, Stéphane Mallat:
Music Generation and Transformation with Moment Matching-Scattering Inverse Networks. ISMIR 2018: 327-333 - [i28]Michael Eickenberg, Georgios Exarchakis, Matthew J. Hirn, Stéphane Mallat, Louis Thiry:
Solid Harmonic Wavelet Scattering for Predictions of Molecule Properties. CoRR abs/1805.00571 (2018) - [i27]Tomás Angles, Stéphane Mallat:
Generative networks as inverse problems with Scattering transforms. CoRR abs/1805.06621 (2018) - [i26]Joakim Andén, Vincent Lostanlen, Stéphane Mallat:
Classification with Joint Time-Frequency Scattering. CoRR abs/1807.08869 (2018) - [i25]Stéphane Mallat, Sixin Zhang, Gaspar Rochette:
Phase Harmonics and Correlation Invariants in Convolutional Neural Networks. CoRR abs/1810.12136 (2018) - [i24]Antoine Brochard, Bartlomiej Blaszczyszyn, Stéphane Mallat, Sixin Zhang:
Statistical learning of geometric characteristics of wireless networks. CoRR abs/1812.08265 (2018) - [i23]Mathieu Andreux
Kymatio: Scattering Transforms in Python. CoRR abs/1812.11214 (2018) - 2017
- [j29]Matthew J. Hirn
Wavelet Scattering Regression of Quantum Chemical Energies. Multiscale Model. Simul. 15(2): 827-863 (2017) - [c37]Michael Eickenberg, Georgios Exarchakis, Matthew J. Hirn, Stéphane Mallat:
Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities. NIPS 2017: 6540-6549 - [i22]Jörn-Henrik Jacobsen, Edouard Oyallon, Stéphane Mallat, Arnold W. M. Smeulders:
Multiscale Hierarchical Convolutional Networks. CoRR abs/1703.04140 (2017) - 2016
- [j28]Guy Wolf, Stéphane Mallat, Shihab A. Shamma:
Rigid Motion Model for Audio Source Separation. IEEE Trans. Signal Process. 64(7): 1822-1831 (2016) - [i21]Vincent Lostanlen, Stéphane Mallat:
Wavelet Scattering on the Pitch Spiral. CoRR abs/1601.00287 (2016) - [i20]Stéphane Mallat:
Understanding Deep Convolutional Networks. CoRR abs/1601.04920 (2016) - [i19]Ivan Dokmanic, Joan Bruna, Stéphane Mallat, Maarten V. de Hoop:
Inverse Problems with Invariant Multiscale Statistics. CoRR abs/1609.05502 (2016) - 2015
- [j27]Irène Waldspurger, Alexandre d'Aspremont, Stéphane Mallat:
Phase recovery, MaxCut and complex semidefinite programming. Math. Program. 149(1-2): 47-81 (2015) - [j26]Ronen Talmon, Stéphane Mallat, Hitten Zaveri, Ronald R. Coifman:
Manifold Learning for Latent Variable Inference in Dynamical Systems. IEEE Trans. Signal Process. 63(15): 3843-3856 (2015) - [c36]Edouard Oyallon, Stéphane Mallat:
Deep roto-translation scattering for object classification. CVPR 2015: 2865-2873 - [c35]Joakim Andén, Vincent Lostanlen, Stéphane Mallat:
Joint time-frequency scattering for audio classification. MLSP 2015: 1-6 - [i18]Matthew J. Hirn, Nicolas Poilvert, Stéphane Mallat:
Quantum Energy Regression using Scattering Transforms. CoRR abs/1502.02077 (2015) - [i17]Vincent Lostanlen, Stéphane Mallat:
Transformée en scattering sur la spirale temps-chroma-octave. CoRR abs/1509.00334 (2015) - [i16]Xiuyuan Cheng, Xu Chen, Stéphane Mallat:
Deep Haar Scattering Networks. CoRR abs/1509.09187 (2015) - [i15]Joakim Andén, Vincent Lostanlen, Stéphane Mallat:
Joint Time-Frequency Scattering for Audio Classification. CoRR abs/1512.02125 (2015) - 2014
- [j25]Václav Chudácek, Joakim Andén, Stéphane Mallat, Patrice Abry
Scattering Transform for Intrapartum Fetal Heart Rate Variability Fractal Analysis: A Case-Control Study. IEEE Trans. Biomed. Eng. 61(4): 1100-1108 (2014) - [j24]Joakim Andén, Stéphane Mallat:
Deep Scattering Spectrum. IEEE Trans. Signal Process. 62(16): 4114-4128 (2014) - [c34]Václav Chudácek, Ronen Talmon, Joakim Andén, Stéphane Mallat, Ronald R. Coifman, Patrice Abry
Low dimensional manifold embedding for scattering coefficients of intrapartum fetale heart rate variability. EMBC 2014: 6373-6376 - [c33]Guy Wolf, Stéphane Mallat, Shihab A. Shamma:
Audio source separation with time-frequency velocities. MLSP 2014: 1-6 - [c32]Xu Chen, Xiuyuan Cheng, Stéphane Mallat:
Unsupervised Deep Haar Scattering on Graphs. NIPS 2014: 1709-1717 - [c31]Edouard Oyallon, Stéphane Mallat, Laurent Sifre:
Generic Deep Networks with Wavelet Scattering. ICLR (Workshop Poster) 2014 - [i14]Laurent Sifre, Stéphane Mallat:
Rigid-Motion Scattering for Texture Classification. CoRR abs/1403.1687 (2014) - [i13]Stéphane Mallat, Irène Waldspurger:
Phase retrieval for the Cauchy wavelet transform. CoRR abs/1404.1183 (2014) - [i12]Xu Chen, Xiuyuan Cheng, Stéphane Mallat:
Unsupervised Learning by Deep Scattering Contractions. CoRR abs/1406.2390 (2014) - [i11]Edouard Oyallon, Stéphane Mallat:
Deep Roto-Translation Scattering for Object Classification. CoRR abs/1412.8659 (2014) - 2013
- [j23]Joan Bruna, Stéphane Mallat:
Invariant Scattering Convolution Networks. IEEE Trans. Pattern Anal. Mach. Intell. 35(8): 1872-1886 (2013) - [c30]Laurent Sifre, Stéphane Mallat:
Rotation, Scaling and Deformation Invariant Scattering for Texture Discrimination. CVPR 2013: 1233-1240 - [c29]Václav Chudácek, Joakim Andén, Stéphane Mallat, Patrice Abry
Scattering transform for intrapartum fetal heart rate characterization and acidosis detection. EMBC 2013: 2898-2901 - [c28]Carlo Bauge, Mathieu Lagrange, Joakim Andén, Stéphane Mallat:
Representing environmental sounds using the separable scattering transform. ICASSP 2013: 8667-8671 - [i10]Joakim Andén, Stéphane Mallat:
Deep Scattering Spectrum. CoRR abs/1304.6763 (2013) - [i9]Stéphane Mallat:
Deep Learning by Scattering. CoRR abs/1306.5532 (2013) - [i8]Habib Ammari, Stéphane Mallat, Irène Waldspurger, Han Wang:
Wavelet methods for shape perception in electro-sensing. CoRR abs/1310.2842 (2013) - [i7]Joan Bruna, Stéphane Mallat:
Audio Texture Synthesis with Scattering Moments. CoRR abs/1311.0407 (2013) - 2012
- [j22]Guoshen Yu, Guillermo Sapiro, Stéphane Mallat:
Solving Inverse Problems With Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity. IEEE Trans. Image Process. 21(5): 2481-2499 (2012) - [c27]Laurent Sifre, Stéphane Mallat:
Combined scattering for rotation invariant texture analysis. ESANN 2012 - [i6]Joan Bruna, Stéphane Mallat:
Invariant Scattering Convolution Networks. CoRR abs/1203.1513 (2012) - 2011
- [j21]Charles Dossal, Erwan Le Pennec
Bandlet image estimation with model selection. Signal Process. 91(12): 2743-2753 (2011) - [c26]Joan Bruna, Stéphane Mallat:
Classification with scattering operators. CVPR 2011: 1561-1566 - [c25]Joakim Andén, Stéphane Mallat:
Multiscale Scattering for Audio Classification. ISMIR 2011: 657-662 - [c24]Joan Bruna, Stéphane Mallat:
Classification with invariant scattering representations. IVMSP 2011: 99-104 - [i5]Stéphane Mallat:
Group Invariant Scattering. CoRR abs/1101.2286 (2011) - [i4]Joan Bruna, Stéphane Mallat:
Geometric Models with Co-occurrence Groups. CoRR abs/1101.5766 (2011) - [i3]Joan Bruna, Stéphane Mallat:
Classification with Invariant Scattering Representations. CoRR abs/1112.1120 (2011) - 2010
- [j20]Stéphane Mallat, Guoshen Yu:
Super-Resolution With Sparse Mixing Estimators. IEEE Trans. Image Process. 19(11): 2889-2900 (2010) - [c23]Joan Bruna, Stéphane Mallat:
Geometric models with co-occurrence groups. ESANN 2010 - [c22]Guoshen Yu, Guillermo Sapiro, Stéphane Mallat:
Image modeling and enhancement via structured sparse model selection. ICIP 2010: 1641-1644 - [i2]Guoshen Yu, Guillermo Sapiro, Stéphane Mallat:
Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity. CoRR abs/1006.3056 (2010) - [i1]Joan Bruna, Stéphane Mallat:
Classification with Scattering Operators. CoRR abs/1011.3023 (2010)
2000 – 2009
- 2009
- [b2]Stéphane Mallat:
A Wavelet Tour of Signal Processing - The Sparse Way, 3rd Edition. Academic Press 2009, ISBN 978-0-12-374370-1, pp. I-XX, 1-805 - [c21]Stéphane Mallat, Guoshen Yu:
Structured pursuits for geometric super-resolution. ICIP 2009: 1477-1480 - 2008
- [j19]Guoshen Yu, Stéphane Mallat, Emmanuel Bacry:
Audio Denoising by Time-Frequency Block Thresholding. IEEE Trans. Signal Process. 56(5): 1830-1839 (2008) - 2007
- [j18]Stéphane Mallat, Gabriel Peyré
A review of Bandlet methods for geometrical image representation. Numer. Algorithms 44(3): 205-234 (2007) - [c20]Guoshen Yu, Emmanuel Bacry, Stéphane Mallat:
Audio Signal Denoising with Complex Wavelets and Adaptive Block Attenuation. ICASSP (3) 2007: 869-872 - 2005
- [j17]Erwan Le Pennec
Bandelet Image Approximation and Compression. Multiscale Model. Simul. 4(3): 992-1039 (2005) - [j16]Erwan Le Pennec
Sparse geometric image representations with bandelets. IEEE Trans. Image Process. 14(4): 423-438 (2005) - [j15]Gabriel Peyré
Surface compression with geometric bandelets. ACM Trans. Graph. 24(3): 601-608 (2005) - [c19]Gabriel Peyré, Stéphane Mallat:
Discrete bandelets with geometric orthogonal filters. ICIP (1) 2005: 65-68 - 2003
- [j14]Jérôme Kalifa, Stéphane Mallat, Bernard Rougé:
Deconvolution by thresholding in mirror wavelet bases. IEEE Trans. Image Process. 12(4): 446-457 (2003) - [j13]David L. Donoho, Stéphane Mallat, Rainer von Sachs, Yann Samuelides:
Locally stationary covariance and signal estimation with macrotiles. IEEE Trans. Signal Process. 51(3): 614-627 (2003) - [c18]Erwan Le Pennec, Stéphane Mallat:
Geometrical image compression with bandelets. VCIP 2003: 1273-1286 - 2002
- [j12]Maureen Clerc
The Texture Gradient Equation for Recovering Shape from Texture. IEEE Trans. Pattern Anal. Mach. Intell. 24(4): 536-549 (2002) - 2001
- [c17]Erwan Le Pennec, Stéphane Mallat:
Bandelet representations for image compression. ICIP (1) 2001: 12 - 2000
- [c16]Erwan Le Pennec, Stéphane Mallat:
Image Compression with Geometrical Wavelets. ICIP 2000: 661-664
1990 – 1999
- 1999
- [b1]Stéphane Mallat:
A Wavelet Tour of Signal Processing, 2nd Edition. Academic Press 1999, ISBN 978-0-12-466606-1, pp. I-XXIV, 1-637 - [j11]Seema Jaggi, William Clement Karl
Silhouette recognition using high-resolution pursuit. Pattern Recognit. 32(5): 753-771 (1999) - [j10]Hamid Krim, Dewey Tucker, Stéphane Mallat, David L. Donoho:
On denoising and best signal representation. IEEE Trans. Inf. Theory 45(7): 2225-2238 (1999) - [c15]Maureen Clerc, Stéphane Mallat:
Shape from Texture through Deformations. ICCV 1999: 405-410 - [c14]Jérôme Kalifa, Stéphane Mallat:
Thresholding estimators for minimax restoration and deconvolution. NSIP 1999: 1-5 - 1998
- [j9]Stéphane Mallat, Frédéric Falzon:
Analysis of low bit rate image transform coding. IEEE Trans. Signal Process. 46(4): 1027-1042 (1998) - [c13]Christophe P. Bernard, Stéphane Mallat, Jean-Jacques E. Slotine:
Wavelet interpolation networks. ESANN 1998: 49-52 - [c12]Jérôme Kalifa, Stéphane Mallat, Bernard Rougé:
Image Deconvolution in Mirror Wavelet Bases. ICIP (1) 1998: 565-569 - [c11]Frédéric Falzon, Stéphane Mallat:
Low bit rate image coding over bases. ICPR 1998: 1260-1263 - 1996
- [j8]Stéphane Mallat:
Wavelets for a vision. Proc. IEEE 84(4): 604-614 (1996) - [c10]Rémi Gribonval, Philippe Depalle, Xavier Rodet, Emmanuel Bacry, Stéphane Mallat:
Sound Signals Decomposition Using a High Resolution Matching Pursuit. ICMC 1996 - 1995
- [c9]Rachel E. Learned, Stéphane Mallat, Bernhard Claus, Alan S. Willsky:
Geometric interpretation of multiaccess joint detection and the alternating projection algorithm. ICASSP 1995: 1193-1196 - [c8]Hamid Krim, Stéphane Mallat, David L. Donoho, Alan S. Willsky:
Best basis algorithm for signal enhancement. ICASSP 1995: 1561-1564 - [c7]F. Bergeaud, Stéphane Mallat:
Matching pursuit of images. ICIP 1995: 53-56 - [c6]Seema Jaggi, Alan S. Willsky, William Clement Karl, Stéphane Mallat:
Multiscale geometrical feature extraction and object recognition with wavelets and morphology. ICIP (3) 1995: 372-375 - 1993
- [j7]Stéphane Mallat, Zhifeng Zhang:
Matching pursuits with time-frequency dictionaries. IEEE Trans. Signal Process. 41(12): 3397-3415 (1993) - [c5]Stéphane Mallat, Zhifeng Zhang:
Adaptive time-frequency transform. ICASSP (3) 1993: 241-244 - 1992
- [j6]Stéphane Mallat, Sifen Zhong:
Characterization of Signals from Multiscale Edges. IEEE Trans. Pattern Anal. Mach. Intell. 14(7): 710-732 (1992) - [j5]Ingrid Daubechies, Stéphane Mallat, Alan S. Willsky:
Introduction to the special issue on wavelet transforms and multiresolution signal analysis. IEEE Trans. Inf. Theory 38(2): 529-532 (1992) - [j4]Stéphane Mallat, Wen-Liang Hwang
Singularity detection and processing with wavelets. IEEE Trans. Inf. Theory 38(2): 617-643 (1992) - [c4]Wen-Liang Hwang, Stéphane Mallat:
Singularities and noise discrimination with wavelets. ICASSP 1992: 377-380 - 1991
- [j3]Stéphane Mallat:
Zero-crossings of a wavelet transform. IEEE Trans. Inf. Theory 37(4): 1019-1033 (1991) - [c3]Stéphane Mallat, Sifen Zhong:
Compact image coding from edges with wavelets. ICASSP 1991: 2745-2748 - 1990
- [c2]Sifen Zhong, Stéphane Mallat:
Compact image representation from multiscale edges. ICCV 1990: 522-525 - [c1]Stéphane Mallat, Sifen Zhong:
Signal characterization from multiscale edges. ICPR (1) 1990: 891-896
1980 – 1989
- 1989
- [j2]Stéphane Mallat:
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation. IEEE Trans. Pattern Anal. Mach. Intell. 11(7): 674-693 (1989) - [j1]Stéphane Mallat:
Multifrequency channel decompositions of images and wavelet models. IEEE Trans. Acoust. Speech Signal Process. 37(12): 2091-2110 (1989)
Coauthor Index
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