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2020 – today
- 2024
[j31]Nikhil Parthasarathy, Olivier J. Hénaff, Eero P. Simoncelli:
Layerwise complexity-matched learning yields an improved model of cortical area V2. Trans. Mach. Learn. Res. 2024 (2024)- [c80]Zahra Kadkhodaie, Florentin Guth, Eero P. Simoncelli, Stéphane Mallat:
Generalization in diffusion models arises from geometry-adaptive harmonic representations. ICLR 2024 - [i21]Ling-Qi Zhang, Zahra Kadkhodaie, Eero P. Simoncelli, David H. Brainard:
Optimized Linear Measurements for Inverse Problems using Diffusion-Based Image Generation. CoRR abs/2405.17456 (2024) - 2023
- [c79]Zahra Kadkhodaie, Florentin Guth, Stéphane Mallat, Eero P. Simoncelli
:
Learning multi-scale local conditional probability models of images. ICLR 2023 - [c78]Lyndon R. Duong, David Lipshutz, David J. Heeger, Dmitri B. Chklovskii, Eero P. Simoncelli:
Adaptive Whitening in Neural Populations with Gain-modulating Interneurons. ICML 2023: 8902-8921 - [c77]Lyndon R. Duong, Eero P. Simoncelli, Dmitri B. Chklovskii, David Lipshutz:
Adaptive whitening with fast gain modulation and slow synaptic plasticity. NeurIPS 2023 - [c76]Pierre-Étienne H. Fiquet, Eero P. Simoncelli:
A polar prediction model for learning to represent visual transformations. NeurIPS 2023 - [c75]Thomas E. Yerxa, Yilun Kuang, Eero P. Simoncelli, SueYeon Chung:
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations. NeurIPS 2023 - [c74]Jingyang Zhou, Chanwoo Chun, Ajay Subramanian, Eero P. Simoncelli:
Comparing neural models using their perceptual discriminability predictions. UniReps 2023: 170-181 - [i20]Lyndon R. Duong, David Lipshutz, David J. Heeger, Dmitri B. Chklovskii, Eero P. Simoncelli:
Statistical whitening of neural populations with gain-modulating interneurons. CoRR abs/2301.11955 (2023) - [i19]Zahra Kadkhodaie, Florentin Guth, Stéphane Mallat, Eero P. Simoncelli:
Learning multi-scale local conditional probability models of images. CoRR abs/2303.02984 (2023) - [i18]Thomas E. Yerxa, Yilun Kuang, Eero P. Simoncelli, SueYeon Chung:
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations. CoRR abs/2303.03307 (2023) - [i17]Pierre-Étienne H. Fiquet, Eero P. Simoncelli:
Polar Prediction of Natural Videos. CoRR abs/2303.03432 (2023) - [i16]Lyndon R. Duong, Eero P. Simoncelli, Dmitri B. Chklovskii, David Lipshutz:
Adaptive whitening with fast gain modulation and slow synaptic plasticity. CoRR abs/2308.13633 (2023) - [i15]Zahra Kadkhodaie, Florentin Guth, Eero P. Simoncelli, Stéphane Mallat:
Generalization in diffusion models arises from geometry-adaptive harmonic representation. CoRR abs/2310.02557 (2023) - [i14]Nikhil Parthasarathy, Olivier J. Hénaff, Eero P. Simoncelli:
Layerwise complexity-matched learning yields an improved model of cortical area V2. CoRR abs/2312.11436 (2023) - 2022
- [j30]Keyan Ding, Kede Ma, Shiqi Wang, Eero P. Simoncelli:
Image Quality Assessment: Unifying Structure and Texture Similarity. IEEE Trans. Pattern Anal. Mach. Intell. 44(5): 2567-2581 (2022) - [j29]Sreyas Mohan, Ramon Manzorro, Joshua L. Vincent, Binh Tang, Dev Yashpal Sheth, Eero P. Simoncelli, David S. Matteson, Peter A. Crozier, Carlos Fernandez-Granda:
Deep Denoising for Scientific Discovery: A Case Study in Electron Microscopy. IEEE Trans. Computational Imaging 8: 585-597 (2022) - [c73]Eric Wu, Nora Brackbill, Alexander Sher, Alan M. Litke, Eero P. Simoncelli, E. J. Chichilnisky:
Maximum a posteriori natural scene reconstruction from retinal ganglion cells with deep denoiser priors. NeurIPS 2022 - [i13]Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad P. Körding, Alexei A. Koulakov, Yann LeCun, Timothy P. Lillicrap, Adam H. Marblestone, Bruno A. Olshausen, Alexandre Pouget, Cristina Savin, Terrence J. Sejnowski, Eero P. Simoncelli, Sara A. Solla, David Sussillo, Andreas S. Tolias, Doris Tsao:
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR abs/2210.08340 (2022) - 2021
- [j28]Keyan Ding, Kede Ma, Shiqi Wang, Eero P. Simoncelli:
Comparison of Full-Reference Image Quality Models for Optimization of Image Processing Systems. Int. J. Comput. Vis. 129(4): 1258-1281 (2021) - [c72]Dev Yashpal Sheth, Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro, Peter A. Crozier, Mitesh M. Khapra, Eero P. Simoncelli, Carlos Fernandez-Granda:
Unsupervised Deep Video Denoising. ICCV 2021: 1739-1748 - [c71]Colin Bredenberg, Benjamin Lyo, Eero P. Simoncelli, Cristina Savin:
Impression learning: Online representation learning with synaptic plasticity. NeurIPS 2021: 11717-11729 - [c70]Zahra Kadkhodaie, Eero P. Simoncelli:
Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser. NeurIPS 2021: 13242-13254 - [c69]Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro, Peter A. Crozier, Carlos Fernandez-Granda, Eero P. Simoncelli:
Adaptive Denoising via GainTuning. NeurIPS 2021: 23727-23740 - [i12]Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro, Peter A. Crozier, Eero P. Simoncelli, Carlos Fernandez-Granda:
Adaptive Denoising via GainTuning. CoRR abs/2107.12815 (2021) - 2020
- [c68]Sreyas Mohan, Zahra Kadkhodaie, Eero P. Simoncelli, Carlos Fernandez-Granda:
Robust And Interpretable Blind Image Denoising Via Bias-Free Convolutional Neural Networks. ICLR 2020 - [c67]Colin Bredenberg, Eero P. Simoncelli, Cristina Savin:
Learning efficient task-dependent representations with synaptic plasticity. NeurIPS 2020 - [i11]Keyan Ding, Kede Ma, Shiqi Wang, Eero P. Simoncelli:
Image Quality Assessment: Unifying Structure and Texture Similarity. CoRR abs/2004.07728 (2020) - [i10]Keyan Ding, Kede Ma, Shiqi Wang, Eero P. Simoncelli:
Comparison of Image Quality Models for Optimization of Image Processing Systems. CoRR abs/2005.01338 (2020) - [i9]Nikhil Parthasarathy, Eero P. Simoncelli:
Self-Supervised Learning of a Biologically-Inspired Visual Texture Model. CoRR abs/2006.16976 (2020) - [i8]Zahra Kadkhodaie, Eero P. Simoncelli:
Solving Linear Inverse Problems Using the Prior Implicit in a Denoiser. CoRR abs/2007.13640 (2020) - [i7]Sreyas Mohan, Ramon Manzorro, Joshua L. Vincent, Binh Tang, Dev Yashpal Sheth, Eero P. Simoncelli, David S. Matteson, Peter A. Crozier, Carlos Fernandez-Granda:
Deep Denoising For Scientific Discovery: A Case Study In Electron Microscopy. CoRR abs/2010.12970 (2020) - [i6]Dev Yashpal Sheth, Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro, Peter A. Crozier, Mitesh M. Khapra, Eero P. Simoncelli, Carlos Fernandez-Granda:
Unsupervised Deep Video Denoising. CoRR abs/2011.15045 (2020)
2010 – 2019
- 2019
- [c66]Kede Ma, Xuelin Liu, Yuming Fang, Eero P. Simoncelli:
Blind Image Quality Assessment by Learning from Multiple Annotators. ICIP 2019: 2344-2348 - [c65]Caroline Haimerl, Cristina Savin, Eero P. Simoncelli:
Flexible information routing in neural populations through stochastic comodulation. NeurIPS 2019: 14379-14388 - [i5]Sreyas Mohan, Zahra Kadkhodaie, Eero P. Simoncelli, Carlos Fernandez-Granda:
Robust and interpretable blind image denoising via bias-free convolutional neural networks. CoRR abs/1906.05478 (2019) - 2017
- [c64]Johannes Ballé, Valero Laparra, Eero P. Simoncelli:
End-to-end Optimized Image Compression. ICLR 2017 - [c63]Alexander Berardino, Valero Laparra, Johannes Ballé, Eero P. Simoncelli:
Eigen-Distortions of Hierarchical Representations. NIPS 2017: 3530-3539 - [i4]Valero Laparra, Alexander Berardino, Johannes Ballé, Eero P. Simoncelli:
Perceptually Optimized Image Rendering. CoRR abs/1701.06641 (2017) - [i3]Alexander Berardino, Johannes Ballé, Valero Laparra, Eero P. Simoncelli:
Eigen-Distortions of Hierarchical Representations. CoRR abs/1710.02266 (2017) - 2016
- [j27]Marino Pagan, Eero P. Simoncelli, Nicole C. Rust:
Neural Quadratic Discriminant Analysis: Nonlinear Decoding with V1-Like Computation. Neural Comput. 28(11): 2291-2319 (2016) - [c62]Valero Laparra, Johannes Ballé, Alexander Berardino, Eero P. Simoncelli:
Perceptual image quality assessment using a normalized Laplacian pyramid. HVEI 2016: 1-6 - [c61]Johannes Ballé, Valero Laparra, Eero P. Simoncelli:
End-to-end optimization of nonlinear transform codes for perceptual quality. PCS 2016: 1-5 - [c60]Johannes Ballé, Valero Laparra, Eero P. Simoncelli:
Density Modeling of Images using a Generalized Normalization Transformation. ICLR 2016 - [c59]Olivier J. Hénaff, Eero P. Simoncelli:
Geodesics of learned representations. ICLR (Poster) 2016 - [i2]Johannes Ballé, Valero Laparra, Eero P. Simoncelli:
End-to-end optimization of nonlinear transform codes for perceptual quality. CoRR abs/1607.05006 (2016) - [i1]Johannes Ballé, Valero Laparra, Eero P. Simoncelli:
End-to-end Optimized Image Compression. CoRR abs/1611.01704 (2016) - 2015
- [c58]Jesús Malo, Eero P. Simoncelli:
Geometrical and statistical properties of vision models obtained via maximum differentiation. Human Vision and Electronic Imaging 2015: 93940L - [c57]Olivier J. Hénaff, Johannes Ballé, Neil C. Rabinowitz, Eero P. Simoncelli:
The local low-dimensionality of natural images. ICLR 2015 - 2014
- [j26]Deep Ganguli, Eero P. Simoncelli:
Efficient Sensory Encoding and Bayesian Inference with Heterogeneous Neural Populations. Neural Comput. 26(10): 2103-2134 (2014) - [c56]Johannes Ballé, Eero P. Simoncelli:
Learning sparse filter bank transforms with convolutional ICA. ICIP 2014: 4013-4017 - 2012
- [j25]Michael Vidne, Yashar Ahmadian, Jonathon Shlens, Jonathan W. Pillow, Jayant Kulkarni, Alan M. Litke, E. J. Chichilnisky, Eero P. Simoncelli, Liam Paninski:
Modeling the impact of common noise inputs on the network activity of retinal ganglion cells. J. Comput. Neurosci. 33(1): 97-121 (2012) - [c55]Yan Karklin, Chaitanya Ekanadham, Eero P. Simoncelli:
Hierarchical spike coding of sound. NIPS 2012: 3041-3049 - [c54]Brett Vintch, Andrew D. Zaharia, J. Anthony Movshon, Eero P. Simoncelli:
Efficient and direct estimation of a neural subunit model for sensory coding. NIPS 2012: 3113-3121 - 2011
- [j24]Martin Raphan, Eero P. Simoncelli:
Least Squares Estimation Without Priors or Supervision. Neural Comput. 23(2): 374-420 (2011) - [j23]Chaitanya Ekanadham, Daniel Tranchina, Eero P. Simoncelli:
Recovery of Sparse Translation-Invariant Signals With Continuous Basis Pursuit. IEEE Trans. Signal Process. 59(10): 4735-4744 (2011) - [c53]Chaitanya Ekanadham, Daniel Tranchina, Eero P. Simoncelli:
Sparse decomposition of transformation-invariant signals with continuous basis pursuit. ICASSP 2011: 4060-4063 - [c52]Yan Karklin, Eero P. Simoncelli:
Efficient coding of natural images with a population of noisy Linear-Nonlinear neurons. NIPS 2011: 999-1007 - [c51]Chaitanya Ekanadham, Daniel Tranchina, Eero P. Simoncelli:
A blind sparse deconvolution method for neural spike identification. NIPS 2011: 1440-1448 - 2010
- [c50]Umesh Rajashekar, Zhou Wang, Eero P. Simoncelli:
Perceptual quality assessment of color images using adaptive signal representation. Human Vision and Electronic Imaging 2010: 75271 - [c49]Deep Ganguli, Eero P. Simoncelli:
Implicit encoding of prior probabilities in optimal neural populations. NIPS 2010: 658-666
2000 – 2009
- 2009
- [j22]Siwei Lyu, Eero P. Simoncelli:
Nonlinear Extraction of Independent Components of Natural Images Using Radial Gaussianization. Neural Comput. 21(6): 1485-1519 (2009) - [j21]Peggy Seriès, Alan A. Stocker, Eero P. Simoncelli:
Is the Homunculus "Aware" of Sensory Adaptation? Neural Comput. 21(12): 3271-3304 (2009) - [j20]Siwei Lyu, Eero P. Simoncelli:
Modeling Multiscale Subbands of Photographic Images with Fields of Gaussian Scale Mixtures. IEEE Trans. Pattern Anal. Mach. Intell. 31(4): 693-706 (2009) - [c48]Umesh Rajashekar, Zhou Wang, Eero P. Simoncelli:
Quantifying color image distortions based on adaptive spatio-chromatic signal decompositions. ICIP 2009: 2213-2216 - [c47]Fabian H. Sinz, Eero P. Simoncelli, Matthias Bethge:
Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions. NIPS 2009: 1696-1704 - [c46]Josh H. McDermott, Andrew J. Oxenham, Eero P. Simoncelli:
Sound texture synthesis via filter statistics. WASPAA 2009: 297-300 - 2008
- [j19]Martin Raphan, Eero P. Simoncelli:
Optimal Denoising in Redundant Representations. IEEE Trans. Image Process. 17(8): 1342-1352 (2008) - [j18]David K. Hammond, Eero P. Simoncelli:
Image Modeling and Denoising With Orientation-Adapted Gaussian Scale Mixtures. IEEE Trans. Image Process. 17(11): 2089-2101 (2008) - [c45]Siwei Lyu, Eero P. Simoncelli:
Nonlinear image representation using divisive normalization. CVPR 2008 - [c44]Rosa M. Figueras i Ventura, Umesh Rajashekar, Zhou Wang, Eero P. Simoncelli:
Contextually adaptive signal representation using conditional principal component analysis. ICASSP 2008: 877-880 - [c43]Jose A. Guerrero-Colon, Eero P. Simoncelli, Javier Portilla:
Image denoising using mixtures of Gaussian scale mixtures. ICIP 2008: 565-568 - [c42]Siwei Lyu, Eero P. Simoncelli:
Reducing statistical dependencies in natural signals using radial Gaussianization. NIPS 2008: 1009-1016 - 2007
- [c41]Siwei Lyu, Eero P. Simoncelli:
Statistically and perceptually motivated nonlinear image representation. Human Vision and Electronic Imaging 2007: 649207 - [c40]David K. Hammond, Eero P. Simoncelli:
A Machine Learning Framework for Adaptive Combination of Signal Denoising Methods. ICIP (6) 2007: 29-32 - [c39]Martin Raphan, Eero P. Simoncelli:
Optimal Denoising in Redundant Bases. ICIP (3) 2007: 113-116 - [c38]Rosa M. Figueras i Ventura, Eero P. Simoncelli:
Statistically Driven Sparse Image Approximation. ICIP (1) 2007: 461-464 - [c37]Alan Stocker, Eero P. Simoncelli:
A Bayesian Model of Conditioned Perception. NIPS 2007: 1409-1416 - 2006
- [j17]Jesus Malo, Irene Epifanio, Rafael Fonolla Navarro, Eero P. Simoncelli:
Nonlinear image representation for efficient perceptual coding. IEEE Trans. Image Process. 15(1): 68-80 (2006) - [j16]Zhou Wang, Guixing Wu, Hamid R. Sheikh, Eero P. Simoncelli, En-Hui Yang, Alan C. Bovik:
Quality-aware images. IEEE Trans. Image Process. 15(6): 1680-1689 (2006) - [c36]David K. Hammond, Eero P. Simoncelli:
Image Denoising with an Orientation-Adaptive Gaussian Scale Mixture Model. ICIP 2006: 1433-1436 - [c35]Siwei Lyu, Eero P. Simoncelli:
Statistical Modeling of Images with Fields of Gaussian Scale Mixtures. NIPS 2006: 945-952 - [c34]Martin Raphan, Eero P. Simoncelli:
Learning to be Bayesian without Supervision. NIPS 2006: 1145-1152 - 2005
- [j15]Liam Paninski, Jonathan W. Pillow, Eero P. Simoncelli:
Comparing integrate-and-fire models estimated using intracellular and extracellular data. Neurocomputing 65-66: 379-385 (2005) - [c33]Zhou Wang, Eero P. Simoncelli:
Reduced-reference image quality assessment using a wavelet-domain natural image statistic model. Human Vision and Electronic Imaging 2005: 149-159 - [c32]Zhou Wang, Eero P. Simoncelli:
Translation Insensitive Image Similarity in Complex Wavelet Domain. ICASSP (2) 2005: 573-576 - [c31]Nicolas Bonnier, Eero P. Simoncelli:
Locally adaptive multiscale contrast optimization. ICIP (1) 2005: 949-952 - [c30]Zhou Wang, Eero P. Simoncelli:
An adaptive linear system framework for image distortion analysis. ICIP (3) 2005: 1160-1163 - [c29]Alan Stocker, Eero P. Simoncelli:
Sensory Adaptation within a Bayesian Framework for Perception. NIPS 2005: 1289-1296 - 2004
- [j14]Nicole C. Rust, Odelia Schwartz, J. Anthony Movshon, Eero P. Simoncelli:
Spike-triggered characterization of excitatory and suppressive stimulus dimensions in monkey V1. Neurocomputing 58-60: 793-799 (2004) - [j13]Liam Paninski, Jonathan W. Pillow, Eero P. Simoncelli:
Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model. Neural Comput. 16(12): 2533-2561 (2004) - [j12]Hany Farid, Eero P. Simoncelli:
Differentiation of discrete multidimensional signals. IEEE Trans. Image Process. 13(4): 496-508 (2004) - [j11]Zhou Wang, Alan C. Bovik, Hamid R. Sheikh, Eero P. Simoncelli:
Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4): 600-612 (2004) - [c28]Zhou Wang, Eero P. Simoncelli:
Stimulus synthesis for efficient evaluation and refinement of perceptual image quality metrics. Human Vision and Electronic Imaging 2004: 99-108 - [c27]Alan Stocker, Eero P. Simoncelli:
Constraining a Bayesian Model of Human Visual Speed Perception. NIPS 2004: 1361-1368 - [c26]Felix A. Wichmann, Arnulf B. A. Graf, Eero P. Simoncelli, Heinrich H. Bülthoff, Bernhard Schölkopf:
Machine Learning Applied to Perception: Decision Images for Gender Classification. NIPS 2004: 1489-1496 - 2003
- [j10]Jonathan W. Pillow, Eero P. Simoncelli:
Biases in white noise analysis due to non-Poisson spike generation. Neurocomputing 52-54: 109-115 (2003) - [j9]A. Srivastava, A. B. Lee, Eero P. Simoncelli, S.-C. Zhu:
On Advances in Statistical Modeling of Natural Images. J. Math. Imaging Vis. 18(1): 17-33 (2003) - [j8]Javier Portilla, Vasily Strela, Martin J. Wainwright, Eero P. Simoncelli:
Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE Trans. Image Process. 12(11): 1338-1351 (2003) - [c25]Javier Portilla, Eero P. Simoncelli:
Image restoration using Gaussian scale mixtures in the wavelet domain. ICIP (2) 2003: 965-968 - [c24]Jonathan W. Pillow, Liam Paninski, Eero P. Simoncelli:
Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model. NIPS 2003: 1311-1318 - [c23]Zhou Wang, Eero P. Simoncelli:
Local Phase Coherence and the Perception of Blur. NIPS 2003: 1435-1442 - [c22]Roberto Valerio, Eero P. Simoncelli, Rafael Fonolla Navarro:
Directly Invertible Nonlinear Divisive Normalization Pyramid for Image Representation. VLBV 2003: 331-340 - 2001
- [j7]Samuel Mikaelian, Eero P. Simoncelli:
Modeling temporal response characteristics of V1 neurons with a dynamic normalization model. Neurocomputing 38-40: 1461-1467 (2001) - [c21]Vasily Strela, Javier Portilla, Martin J. Wainwright, Eero P. Simoncelli:
Adaptive Wiener denoising using a Gaussian scale mixture model in the wavelet domain. ICIP (2) 2001: 37-40 - [c20]Odelia Schwartz, E. J. Chichilnisky, Eero P. Simoncelli:
Characterizing Neural Gain Control using Spike-triggered Covariance. NIPS 2001: 269-276 - 2000
- [j6]Javier Portilla, Eero P. Simoncelli:
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients. Int. J. Comput. Vis. 40(1): 49-70 (2000) - [c19]Yufeng Liang, Eero P. Simoncelli, Zhibin Lei:
Color Channels Decorrelation by ICA Transformation in the Wavelet Domain for Color Texture Analysis and Synthesis. CVPR 2000: 1606-1610 - [c18]Martin J. Wainwright, Eero P. Simoncelli, Alan S. Willsky:
Random Cascades of Gaussian Scale Mixtures and Their Use in Modeling Natural Images With Application to Denoising. ICIP 2000: 260-263 - [c17]Javier Portilla, Eero P. Simoncelli:
Image Denoising via Adjustment of Wavelet Coefficient Magnitude Correlation. ICIP 2000: 277-280 - [c16]Odelia Schwartz, Eero P. Simoncelli:
Natural Sound Statistics and Divisive Normalization in the Auditory System. NIPS 2000: 166-172
1990 – 1999
- 1999
- [j5]Robert W. Buccigrossi, Eero P. Simoncelli:
Image compression via joint statistical characterization in the wavelet domain. IEEE Trans. Image Process. 8(12): 1688-1701 (1999) - [c15]Martin J. Wainwright, Eero P. Simoncelli:
Scale Mixtures of Gaussians and the Statistics of Natural Images. NIPS 1999: 855-861 - 1998
- [c14]Eero P. Simoncelli, Javier Portilla:
Texture Characterization via Joint Statistics of Wavelet Coefficient Magnitudes. ICIP (1) 1998: 62-66 - [c13]Eero P. Simoncelli, Odelia Schwartz:
Modeling Surround Suppression in V1 Neurons with a Statistically Derived Normalization Model. NIPS 1998: 153-159 - 1997
- [c12]Hany Farid, Eero P. Simoncelli:
Optimally Rotation-Equivariant Directional Derivative Kernels. CAIP 1997: 207-214 - [c11]Jeffrey Mendelsohn, Eero P. Simoncelli, Ruzena Bajcsy:
Discrete-Time Rigidity-Constrained Optical Flow. CAIP 1997: 255-262 - [c10]Robert W. Buccigrossi, Eero P. Simoncelli:
Progressive wavelet image coding based on a conditional probability model. ICASSP 1997: 2957-2960 - [c9]Eero P. Simoncelli, Robert W. Buccigrossi:
Embedded Wavelet Image Compression Based On A Joint Probability Model. ICIP (1) 1997: 640-643 - 1996
- [j4]Eero P. Simoncelli, Hany Farid:
Steerable wedge filters for local orientation analysis. IEEE Trans. Image Process. 5(9): 1377-1382 (1996) - [c8]Eero P. Simoncelli, Hany Farid:
Direct Differential Range Estimation Using Optical Masks. ECCV (2) 1996: 82-93 - [c7]Anestis Karasaridis, Eero P. Simoncelli:
A filter design technique for steerable pyramid image transforms. ICASSP 1996: 2387-2390 - [c6]Eero P. Simoncelli:
A rotation invariant pattern signature. ICIP (3) 1996: 185-188 - [c5]Eero P. Simoncelli, Edward H. Adelson:
Noise removal via Bayesian wavelet coring. ICIP (1) 1996: 379-382 - 1995
- [j3]Jeffry Nimeroff, Eero P. Simoncelli, Julie Dorsey, Norman I. Badler:
Rendering Spaces for Architectural Environments. Presence Teleoperators Virtual Environ. 4(3): 286-296 (1995) - [c4]Eero P. Simoncelli, Hany Farid:
Steerable Wedge Filters. ICCV 1995: 189-194 - [c3]Eero P. Simoncelli, William T. Freeman:
The steerable pyramid: a flexible architecture for multi-scale derivative computation. ICIP (3) 1995: 444-447 - 1994
- [c2]Eero P. Simoncelli:
Design of Multi-Dimensional Derivative Filters. ICIP (1) 1994: 790-794 - 1993
- [b1]Eero P. Simoncelli:
Distributed representation and analysis of visual motion. Massachusetts Institute of Technology, Cambridge, MA, USA, 1993 - 1992
- [j2]Eero P. Simoncelli, William T. Freeman, Edward H. Adelson, David J. Heeger:
Shiftable multiscale transforms. IEEE Trans. Inf. Theory 38(2): 587-607 (1992) - 1991
- [c1]Eero P. Simoncelli, Edward H. Adelson, David J. Heeger:
Probability distributions of optical flow. CVPR 1991: 310-315 - 1990
- [j1]Eero P. Simoncelli, Edward H. Adelson:
Non-separable extensions of quadrature mirror filters to multiple dimensions. Proc. IEEE 78(4): 652-664 (1990)
Coauthor Index
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