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ORCIDJosé M. F. Moura
José Moura 0002
Person information
- affiliation: Carnegie Mellon University, Pittsburgh, PA, USA
Other persons with the same name
- José Moura — disambiguation page
- José André R. S. Moura
![[0000-0002-3516-8781]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-3516-8781")
(aka: José Moura 0001) — ISCTE, University Institute of Lisbon, Portugal
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2020 – today
- 2023
[j148]Athina P. Petropulu, José M. F. Moura, Rabab Kreidieh Ward, Theresa Argiropoulos:
Empowering the Growth of Signal Processing: The evolution of the IEEE Signal Processing Society. IEEE Signal Process. Mag. 40(4): 14-22 (2023)- [j147]Stefan Vlaski, Soummya Kar, Ali H. Sayed, José M. F. Moura:
Networked Signal and Information Processing: Learning by multiagent systems. IEEE Signal Process. Mag. 40(5): 92-105 (2023) - [c263]Sergio Machado, Anirudh Sridhar, Paulo Gil, Jorge Henriques, José M. F. Moura, Augusto Santos:
Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach. AAAI 2023: 9038-9046 - [c262]Wei Li, Fangzhou Wang, José M. F. Moura, R. D. (Shawn) Blanton:
Global Floorplanning via Semidefinite Programming. DAC 2023: 1-6 - [c261]Tong Shen, Yang Li, José M. F. Moura:
Forecasting COVID-19 Dynamics: Clustering, Generalized Spatiotemporal Attention, and Impacts of Mobility and Geographic Proximity. ICDE 2023: 2892-2904 - [i99]Shreyas Chaudhari, Srinivasa Pranav, José M. F. Moura:
Learning Gradients of Convex Functions with Monotone Gradient Networks. CoRR abs/2301.10862 (2023) - [i98]Rajshekhar Das, Jonathan Francis, Sanket Vaibhav Mehta, Jean Oh, Emma Strubell, José M. F. Moura:
Regularizing Self-training for Unsupervised Domain Adaptation via Structural Constraints. CoRR abs/2305.00131 (2023) - 2022
- [j146]John Shi, José M. F. Moura:
Graph Signal Processing: Dualizing GSP Sampling in the Vertex and Spectral Domains. IEEE Trans. Signal Process. 70: 2883-2898 (2022) - [c260]John Shi, José M. F. Moura:
From DSP to GSP: Sampling in Both Domains. IEEECONF 2022: 240-245 - [c259]Shreyas Chaudhari, José M. F. Moura:
Deep Beamforming for Joint Direction of Arrival Estimation and Source Detection. IEEECONF 2022: 1403-1407 - [i97]Sergio Machado, Anirudh Sridhar, Paulo Gil, Jorge Henriques, José M. F. Moura, Augusto Santos:
Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach. CoRR abs/2208.04405 (2022) - [i96]Stefan Vlaski, Soummya Kar, Ali H. Sayed, José M. F. Moura:
Networked Signal and Information Processing. CoRR abs/2210.13767 (2022) - 2021
- [j145]Hagit Messer, Arye Nehorai, Jeffrey L. Krolik, José M. F. Moura, Al Hero, Joseph Tabrikian:
In Remembrance of Peter Schultheiss [In Memoriam]. IEEE Signal Process. Mag. 38(3): 10 (2021) - [c258]Mark Cheung, José M. F. Moura:
Graph Classification: Tradeoffs between Deep Neural Network Architecture and Graph Topology. ACSCC 2021: 454-458 - [c257]Austin Lin, Wendy Summer, John Shi, Mark Cheung, José M. F. Moura:
Using Sparse Spectral Shifts in Graph CNNs. ACSCC 2021: 1536-1540 - [c256]Shreyas Chaudhari, Harideep Nair, José M. F. Moura, John Paul Shen:
Unsupervised Clustering of Time Series Signals Using Neuromorphic Energy-Efficient Temporal Neural Networks. ICASSP 2021: 7873-7877 - [c255]Rajshekhar Das, Yu-Xiong Wang, José M. F. Moura:
On the Importance of Distractors for Few-Shot Classification. ICCV 2021: 9010-9020 - [c254]Yixiong Zou, Shanghang Zhang, Guangyao Chen, Yonghong Tian, Kurt Keutzer, José M. F. Moura:
Annotation-Efficient Untrimmed Video Action Recognition. ACM Multimedia 2021: 487-495 - [c253]Yixiong Zou, Shanghang Zhang, Jianpeng Yu, Yonghong Tian, José M. F. Moura:
Revisiting Mid-Level Patterns for Cross-Domain Few-Shot Recognition. ACM Multimedia 2021: 741-749 - [c252]Alireza Chamanzar, Xujin Liu, Lavender Yao Jiang, Kimon A. Vogt, José M. F. Moura, Pulkit Grover:
Automated, Scalable and Generalizable Deep Learning for Tracking Cortical Spreading Depression Using EEG. NER 2021: 416-419 - [i95]Shreyas Chaudhari, Harideep Nair, José M. F. Moura, John Paul Shen:
Unsupervised Clustering of Time Series Signals using Neuromorphic Energy-Efficient Temporal Neural Networks. CoRR abs/2102.09200 (2021) - [i94]Evgeny Toropov, Paola A. Buitrago, José M. F. Moura:
Shuffler: A Large Scale Data Management Tool for ML in Computer Vision. CoRR abs/2104.05125 (2021) - [i93]Yang Li, Di Wang, José M. F. Moura:
GSA-Forecaster: Forecasting Graph-Based Time-Dependent Data with Graph Sequence Attention. CoRR abs/2104.05914 (2021) - [i92]Rajshekhar Das, Yu-Xiong Wang, José M. F. Moura:
On the Importance of Distractors for Few-Shot Classification. CoRR abs/2109.09883 (2021) - 2020
- [j144]Dusan Jakovetic, Dragana Bajovic, João M. F. Xavier, José M. F. Moura:
Primal-Dual Methods for Large-Scale and Distributed Convex Optimization and Data Analytics. Proc. IEEE 108(11): 1923-1938 (2020) - [j143]Yuan Chen, Soummya Kar, José M. F. Moura:
Resilient Distributed Field Estimation. SIAM J. Control. Optim. 58(3): 1429-1456 (2020) - [j142]Antonio G. Marques, Negar Kiyavash, José M. F. Moura, Dimitri Van De Ville, Rebecca Willett:
Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors]. IEEE Signal Process. Mag. 37(6): 11-13 (2020) - [j141]Mark Cheung, John Shi, Oren Wright, Lavender Yao Jiang, Xujin Liu, José M. F. Moura:
Graph Signal Processing and Deep Learning: Convolution, Pooling, and Topology. IEEE Signal Process. Mag. 37(6): 139-149 (2020) - [j140]João Domingos, José M. F. Moura:
Graph Fourier Transform: A Stable Approximation. IEEE Trans. Signal Process. 68: 4422-4437 (2020) - [c251]Soummya Kar, Markus Püschel, José M. F. Moura:
Finite-Time In-Network Computation of Linear Transforms. ACSSC 2020: 455-459 - [c250]Lavender Yao Jiang, John Shi, Mark Cheung, Oren Wright, José M. F. Moura:
Edge Entropy as an Indicator of the Effectiveness of GNNs over CNNs for Node Classification. ACSSC 2020: 746-750 - [c249]John Shi, Mark Cheung, Wendy Summer, José M. F. Moura:
A Dual Approach to Graph CNNs. ACSSC 2020: 1467-1471 - [c248]Mark Cheung, José M. F. Moura:
Graph Neural Networks for COVID-19 Drug Discovery. IEEE BigData 2020: 5646-5648 - [c247]Yang Li, José M. F. Moura:
Forecaster: A Graph Transformer for Forecasting Spatial and Time-Dependent Data. ECAI 2020: 1293-1300 - [c246]Umang Bhatt, Alice Xiang, Shubham Sharma, Adrian Weller, Ankur Taly, Yunhan Jia, Joydeep Ghosh, Ruchir Puri, José M. F. Moura, Peter Eckersley:
Explainable machine learning in deployment. FAT* 2020: 648-657 - [c245]Yuan Chen, Soummya Kar, José M. F. Moura:
Resilient Distributed Recovery of Large Fields. ICASSP 2020: 4292-4296 - [c244]Brian Davis, Umang Bhatt, Kartikeya Bhardwaj, Radu Marculescu, José M. F. Moura:
On Network Science and Mutual Information for Explaining Deep Neural Networks. ICASSP 2020: 8399-8403 - [c243]Umang Bhatt, Adrian Weller, José M. F. Moura:
Evaluating and Aggregating Feature-based Model Explanations. IJCAI 2020: 3016-3022 - [c242]Yixiong Zou, Shanghang Zhang, Ke Chen, Yonghong Tian, Yaowei Wang, José M. F. Moura:
Compositional Few-Shot Recognition with Primitive Discovery and Enhancing. ACM Multimedia 2020: 156-164 - [i91]Mark Cheung, John Shi, Lavender Yao Jiang, Oren Wright, José M. F. Moura:
Pooling in Graph Convolutional Neural Networks. CoRR abs/2004.03519 (2020) - [i90]Umang Bhatt, Adrian Weller, José M. F. Moura:
Evaluating and Aggregating Feature-based Model Explanations. CoRR abs/2005.00631 (2020) - [i89]Yixiong Zou, Shanghang Zhang, Ke Chen, José M. F. Moura, Yaowei Wang, Yonghong Tian:
Compositional Few-Shot Recognition with Primitive Discovery and Enhancing. CoRR abs/2005.06047 (2020) - [i88]Yixiong Zou, Shanghang Zhang, José M. F. Moura, Jianpeng Yu, Yonghong Tian:
Revisiting Mid-Level Patterns for Distant-Domain Few-Shot Recognition. CoRR abs/2008.03128 (2020) - [i87]Yixiong Zou, Shanghang Zhang, Guangyao Chen, Yonghong Tian, Kurt Keutzer, José M. F. Moura:
Annotation-Efficient Untrimmed Video Action Recognition. CoRR abs/2011.14478 (2020) - [i86]Lavender Yao Jiang, John Shi, Mark Cheung, Oren Wright, José M. F. Moura:
Edge Entropy as an Indicator of the Effectiveness of GNNs over CNNs for Node Classification. CoRR abs/2012.08698 (2020)
2010 – 2019
- 2019
- [j139]Abhishek Das, Satwik Kottur, Khushi Gupta, Avi Singh, Deshraj Yadav, Stefan Lee, José M. F. Moura, Devi Parikh, Dhruv Batra:
Visual Dialog. IEEE Trans. Pattern Anal. Mach. Intell. 41(5): 1242-1256 (2019) - [j138]Yuan Chen, Soummya Kar, José M. F. Moura:
Resilient Distributed Estimation: Sensor Attacks. IEEE Trans. Autom. Control. 64(9): 3772-3779 (2019) - [j137]Dragana Bajovic, José M. F. Moura, Dejan Vukobratovic:
Detecting Random Walks on Graphs With Heterogeneous Sensors. IEEE Trans. Inf. Theory 65(8): 4893-4914 (2019) - [j136]Yuan Chen, Soummya Kar, José M. F. Moura:
Resilient Distributed Parameter Estimation With Heterogeneous Data. IEEE Trans. Signal Process. 67(19): 4918-4933 (2019) - [c241]Umang Bhatt, Pradeep Ravikumar, José M. F. Moura:
Building Human-Machine Trust via Interpretability. AAAI 2019: 9919-9920 - [c240]Umang Bhatt, Brian Davis, José M. F. Moura:
Diagnostic Model Explanations: A Medical Narrative. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c239]John Shi, José M. F. Moura:
Topics in Graph Signal Processing: Convolution and Modulation. ACSSC 2019: 457-461 - [c238]Mark Cheung, John Shi, Lavender Yao Jiang, Oren Wright, José M. F. Moura:
Pooling in Graph Convolutional Neural Networks. ACSSC 2019: 462-466 - [c237]Brian Swenson, Soummya Kar, H. Vincent Poor, José M. F. Moura:
Distributed Global Optimization by Annealing. CAMSAP 2019: 181-185 - [c236]Brian Swenson, Soummya Kar, H. Vincent Poor, José M. F. Moura:
Annealing for Distributed Global Optimization. CDC 2019: 3018-3025 - [c235]Liang-Yan Gui, David A. Sepiashvili, José M. F. Moura:
Invariance to Affine-Permutation Distortions. CVPR Workshops 2019: 1157-1161 - [c234]Yuan Chen, Soummya Kar, José M. F. Moura:
Secure Analytics and Resilient Inference for the Internet of Things. ICASSP 2019: 8394-8398 - [c233]Satwik Kottur, José M. F. Moura, Devi Parikh, Dhruv Batra, Marcus Rohrbach:
CLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog. NAACL-HLT (1) 2019: 582-595 - [c232]Evgeny Toropov, Paola A. Buitrago, José M. F. Moura:
Shuffler: A Large Scale Data Management Tool for Machine Learning in Computer Vision. PEARC 2019: 23:1-23:8 - [i85]Brian Davis, Umang Bhatt, Kartikeya Bhardwaj, Radu Marculescu, José M. F. Moura:
NIF: A Framework for Quantifying Neural Information Flow in Deep Networks. CoRR abs/1901.08557 (2019) - [i84]Umang Bhatt, Pradeep Ravikumar, José M. F. Moura:
Towards Aggregating Weighted Feature Attributions. CoRR abs/1901.10040 (2019) - [i83]Satwik Kottur, José M. F. Moura, Devi Parikh, Dhruv Batra, Marcus Rohrbach:
CLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog. CoRR abs/1903.03166 (2019) - [i82]Brian Swenson, Soummya Kar, H. Vincent Poor, José M. F. Moura:
Distributed Global Optimization by Annealing. CoRR abs/1907.08802 (2019) - [i81]Yang Li, José M. F. Moura:
Forecaster: A Graph Transformer for Forecasting Spatial and Time-Dependent Data. CoRR abs/1909.04019 (2019) - [i80]Umang Bhatt, Alice Xiang, Shubham Sharma, Adrian Weller, Ankur Taly, Yunhan Jia, Joydeep Ghosh, Ruchir Puri, José M. F. Moura, Peter Eckersley:
Explainable Machine Learning in Deployment. CoRR abs/1909.06342 (2019) - [i79]Yuan Chen, Soummya Kar, José M. F. Moura:
Resilient Distributed Recovery of Large Fields. CoRR abs/1910.08841 (2019) - [i78]Dusan Jakovetic, Dragana Bajovic, João M. F. Xavier, José M. F. Moura:
Primal-dual optimization methods for large-scale and distributed data analytics. CoRR abs/1912.08546 (2019) - 2018
- [j135]Antonio Ortega, Pascal Frossard, Jelena Kovacevic, José M. F. Moura, Pierre Vandergheynst:
Graph Signal Processing: Overview, Challenges, and Applications. Proc. IEEE 106(5): 808-828 (2018) - [j134]Sam Safavi, Usman A. Khan, Soummya Kar, José M. F. Moura:
Distributed Localization: A Linear Theory. Proc. IEEE 106(7): 1204-1223 (2018) - [j133]Franz Franchetti, José M. F. Moura, David A. Padua, Jack J. Dongarra:
From High-Level Specification to High-Performance Code. Proc. IEEE 106(11): 1875-1878 (2018) - [j132]Franz Franchetti, Tze Meng Low, Doru-Thom Popovici, Richard Michael Veras, Daniele G. Spampinato, Jeremy R. Johnson, Markus Püschel, James C. Hoe, José M. F. Moura:
SPIRAL: Extreme Performance Portability. Proc. IEEE 106(11): 1935-1968 (2018) - [j131]Yuan Chen, Soummya Kar, José M. F. Moura:
The Internet of Things: Secure Distributed Inference. IEEE Signal Process. Mag. 35(5): 64-75 (2018) - [j130]Yuan Chen, Soummya Kar, José M. F. Moura:
Cyber-Physical Attacks With Control Objectives. IEEE Trans. Autom. Control. 63(5): 1418-1425 (2018) - [j129]Yuan Chen, Soummya Kar, José M. F. Moura:
Optimal Attack Strategies Subject to Detection Constraints Against Cyber-Physical Systems. IEEE Trans. Control. Netw. Syst. 5(3): 1157-1168 (2018) - [j128]June Zhang, José M. F. Moura:
Cascading Edge Failures: A Dynamic Network Process. IEEE Trans. Netw. Sci. Eng. 5(4): 288-300 (2018) - [j127]Stephen Kruzick, Sérgio Pequito, Soummya Kar, José M. F. Moura, António Pedro Aguiar:
Structurally Observable Distributed Networks of Agents Under Cost and Robustness Constraints. IEEE Trans. Signal Inf. Process. over Networks 4(2): 236-247 (2018) - [j126]Stephen Kruzick, José M. F. Moura:
Optimal Filter Design for Signal Processing on Random Graphs: Accelerated Consensus. IEEE Trans. Signal Process. 66(5): 1258-1272 (2018) - [j125]Yuan Chen, Soummya Kar, José M. F. Moura:
Resilient Distributed Estimation Through Adversary Detection. IEEE Trans. Signal Process. 66(9): 2455-2469 (2018) - [j124]Jonathan Mei, José M. F. Moura:
SILVar: Single Index Latent Variable Models. IEEE Trans. Signal Process. 66(11): 2790-2803 (2018) - [c231]John Shi, Mark Cheung, Jian Du, José M. F. Moura:
Classification with Vertex-Based Graph Convolutional Neural Networks. ACSSC 2018: 752-756 - [c230]Yuan Chen, Soummya Kar, José M. F. Moura:
Attack Resilient Distributed Estimation: A Consensus+Innovations Approach. ACC 2018: 1015-1020 - [c229]Yuan Chen, Soummya Kar, José M. F. Moura:
Resilient Distributed Estimation: Exponential Convergence Under Sensor Attacks. CDC 2018: 7275-7282 - [c228]Shanghang Zhang, Xiaohui Shen, Zhe Lin, Radomír Mech, João Paulo Costeira, José M. F. Moura:
Learning to Understand Image Blur. CVPR 2018: 6586-6595 - [c227]Stephen Kruzick, José M. F. Moura:
Spectral Statistics of Directed Networks with Random Link Model Transpose-Asymmetry. DSW 2018: 26-30 - [c226]Jian Du, John Shi, Soummya Kar, José M. F. Moura:
On Graph Convolution for Graph CNNs. DSW 2018: 239-243 - [c225]Satwik Kottur, José M. F. Moura, Devi Parikh, Dhruv Batra, Marcus Rohrbach:
Visual Coreference Resolution in Visual Dialog Using Neural Module Networks. ECCV (15) 2018: 160-178 - [c224]Liang-Yan Gui, Yu-Xiong Wang, Deva Ramanan, José M. F. Moura:
Few-Shot Human Motion Prediction via Meta-learning. ECCV (8) 2018: 441-459 - [c223]Liang-Yan Gui, Yu-Xiong Wang, Xiaodan Liang, José M. F. Moura:
Adversarial Geometry-Aware Human Motion Prediction. ECCV (4) 2018: 823-842 - [c222]Jonathan Mei, José M. F. Moura:
Single Index Latent Variable Models for Network Topology Inference. GlobalSIP 2018: 703-707 - [c221]June Zhang, José M. F. Moura:
Who is More at Risk in Heterogenous Networks? ICASSP 2018: 4174-4178 - [c220]Rajshekhar Das, Akshay Gadre, Shanghang Zhang, Swarun Kumar, José M. F. Moura:
A Deep Learning Approach to IoT Authentication. ICC 2018: 1-6 - [c219]Han Zhao, Shanghang Zhang, Guanhang Wu, João Paulo Costeira, José M. F. Moura, Geoffrey J. Gordon:
Multiple Source Domain Adaptation with Adversarial Learning. ICLR (Workshop) 2018 - [c218]Liang-Yan Gui, Kevin Zhang, Yu-Xiong Wang, Xiaodan Liang, José M. F. Moura, Manuela Veloso:
Teaching Robots to Predict Human Motion. IROS 2018: 562-567 - [c217]Han Zhao, Shanghang Zhang, Guanhang Wu, José M. F. Moura, João Paulo Costeira, Geoffrey J. Gordon:
Adversarial Multiple Source Domain Adaptation. NeurIPS 2018: 8568-8579 - [c216]Stephen Kruzick, José M. F. Moura:
Optimal Filter Design for Consensus on Random Directed Graphs. SSP 2018: 16-20 - [c215]Sam Safavi, Usman A. Khan, Soummya Kar, José M. F. Moura:
Linear Distributed Algorithms For Localization In Mobile Networks. SSP 2018: 638-642 - [c214]Liang-Yan Gui, Liangke Gui, Yu-Xiong Wang, Louis-Philippe Morency, José M. F. Moura:
Factorized Convolutional Networks: Unsupervised Fine-Tuning for Image Clustering. WACV 2018: 1205-1214 - [i77]Jian Du, Shaodan Ma, Yik-Chung Wu, Soummya Kar, José M. F. Moura:
Convergence Analysis of Belief Propagation on Gaussian Graphical Models. CoRR abs/1801.06430 (2018) - [i76]Sam Safavi, Usman A. Khan, Soummya Kar, José M. F. Moura:
Localization in internets of mobile agents: A linear approach. CoRR abs/1802.04345 (2018) - [i75]Jonathan Mei, José M. F. Moura:
EigenNetworks. CoRR abs/1806.01455 (2018) - [i74]Yuan Chen, Soummya Kar, José M. F. Moura:
The Internet of Things: Secure Distributed Inference. CoRR abs/1806.09199 (2018) - [i73]Jonathan Mei, José M. F. Moura:
Single Index Latent Variable Models for Network Topology Inference. CoRR abs/1807.00002 (2018) - [i72]Satwik Kottur, José M. F. Moura, Devi Parikh, Dhruv Batra, Marcus Rohrbach:
Visual Coreference Resolution in Visual Dialog using Neural Module Networks. CoRR abs/1809.01816 (2018) - 2017
- [j123]June Zhang, José M. F. Moura:
Contact process with exogenous infection and the scaled SIS process. J. Complex Networks 5(5): 712-733 (2017) - [j122]Augusto Almeida Santos, Michele Nogueira, José M. F. Moura:
A Stochastic Adaptive Model to Explore Mobile Botnet Dynamics. IEEE Commun. Lett. 21(4): 753-756 (2017) - [j121]Andrew J. Sonta, Rishee K. Jain, Rimas Gulbinas, José M. F. Moura, John E. Taylor:
OESPG: Computational Framework for Multidimensional Analysis of Occupant Energy Use Data in Commercial Buildings. J. Comput. Civ. Eng. 31(4) (2017) - [j120]Jian Du, Shaodan Ma, Yik-Chung Wu, Soummya Kar, José M. F. Moura:
Convergence Analysis of Distributed Inference with Vector-Valued Gaussian Belief Propagation. J. Mach. Learn. Res. 18: 172:1-172:38 (2017) - [j119]Joya A. Deri, José M. F. Moura:
Spectral Projector-Based Graph Fourier Transforms. IEEE J. Sel. Top. Signal Process. 11(6): 785-795 (2017) - [j118]Liangyan Gui, Xiaoying Tang, José M. F. Moura:
Geodesic distance on a Grassmannian for monitoring the progression of Alzheimer's disease. NeuroImage 146: 1016-1024 (2017) - [j117]Yuan Chen, Soummya Kar, José M. F. Moura:
Dynamic Attack Detection in Cyber-Physical Systems With Side Initial State Information. IEEE Trans. Autom. Control. 62(9): 4618-4624 (2017) - [j116]Subhro Das, José M. F. Moura:
Consensus+Innovations Distributed Kalman Filter With Optimized Gains. IEEE Trans. Signal Process. 65(2): 467-481 (2017) - [j115]Jonathan Mei, José M. F. Moura:
Signal Processing on Graphs: Causal Modeling of Unstructured Data. IEEE Trans. Signal Process. 65(8): 2077-2092 (2017) - [c213]Yuan Chen, Soummya Kar, José M. F. Moura:
Detecting adversaries in distributed estimation. ACSSC 2017: 1384-1388 - [c212]Jian Du, Soummya Kar, José M. F. Moura:
Distributed convergence verification for Gaussian belief propagation. ACSSC 2017: 1439-1443 - [c211]Stephen Kruzick, José M. F. Moura:
Consensus state gram matrix estimation for stochastic switching networks from spectral distribution moments. ACSSC 2017: 1455-1459 - [c210]Stephen Kruzick, José M. F. Moura:
Graph signal processing: Filter design and spectral statistics. CAMSAP 2017: 1-5 - [c209]Abhishek Das, Satwik Kottur, Khushi Gupta, Avi Singh, Deshraj Yadav, José M. F. Moura, Devi Parikh, Dhruv Batra:
Visual Dialog. CVPR 2017: 1080-1089 - [c208]Shanghang Zhang,