Maximum likelihood network topology identification from edge-based unicast measurements. - Mark Coates; Rui M. Castro; Robert D. Nowak; Manik Gadhiok; Ryan King; Yolanda Tsang (SIGMETRICS, 2002)

Likelihood Based Hierarchical Clustering and Network Topology Identification. - Rui M. Castro; Robert D. Nowak (EMMCVPR, 2003)

Coarse-to-fine manifold learning [image processing example]. - Rui M. Castro; Rebecca Willett; Robert D. Nowak (ICASSP (3), 2004)

Likelihood based hierarchical clustering. - Rui M. Castro; Mark Coates; Robert D. Nowak (IEEE Trans. Signal Process., 2004)

Faster Rates in Regression via Active Learning. - Rui M. Castro; Rebecca Willett; Robert D. Nowak (NIPS, 2005)

Compressed sensing in noisy imaging environments. - Jarvis D. Haupt; Rui M. Castro; Robert D. Nowak (Computational Imaging, 2006)

Compressed Sensing Vs. Active Learning. - Rui M. Castro; Jarvis D. Haupt; Robert D. Nowak (ICASSP (3), 2006)

Adaptive discovery of sparse signals in noise. - Jarvis D. Haupt; Rui M. Castro; Robert D. Nowak (ACSCC, 2008)

Finding needles in noisy haystacks. - Rui M. Castro; Jarvis D. Haupt; Robert D. Nowak; Gil M. Raz (ICASSP, 2008)

Human Active Learning. - Rui M. Castro; Charles Kalish; Robert D. Nowak; Ruichen Qian; Timothy T. Rogers; Xiaojin Zhu 001 (NIPS, 2008)

Minimax Bounds for Active Learning. - Rui M. Castro; Robert D. Nowak (IEEE Trans. Inf. Theory, 2008)

Distilled sensing: selective sampling for sparse signal recovery. - Jarvis D. Haupt; Rui M. Castro; Robert D. Nowak (AISTATS, 2009)

Adaptive spectrum sensing for agile cognitive radios. - Ali Tajer; Rui M. Castro; Xiaodong Wang 001 (ICASSP, 2010)

Improved bounds for sparse recovery from adaptive measurements. - Jarvis D. Haupt; Rui M. Castro; Robert D. Nowak (ISIT, 2010)

Efficient Decentralized Approximation via Selective Gossip. - Deniz Üstebay; Rui M. Castro; Michael G. Rabbat (IEEE J. Sel. Top. Signal Process., 2011)

Distilled Sensing: Adaptive Sampling for Sparse Detection and Estimation. - Jarvis D. Haupt; Rui M. Castro; Robert D. Nowak (IEEE Trans. Inf. Theory, 2011)

Joint Optimization and Variable Selection of High-dimensional Gaussian Processes. - Bo Chen 019; Rui M. Castro; Andreas Krause 001 (ICML, 2012)

Sequentially designed compressed sensing. - Jarvis D. Haupt; Richard G. Baraniuk; Rui M. Castro; Robert D. Nowak (SSP, 2012)

Adaptive Sensing of Congested Spectrum Bands. - Ali Tajer; Rui M. Castro; Xiaodong Wang 001 (IEEE Trans. Inf. Theory, 2012)

Detection of Correlations With Adaptive Sensing. - Rui M. Castro; Gábor Lugosi; Pierre-André Savalle (IEEE Trans. Inf. Theory, 2014)

Adaptive Sensing for Estimation of Structured Sparse Signals. - Rui M. Castro; Ervin Tanczos (IEEE Trans. Inf. Theory, 2015)

Adaptive Compressed Sensing for Support Recovery of Structured Sparse Sets. - Rui M. Castro; Ervin Tanczos (IEEE Trans. Inf. Theory, 2017)

Restricted Boltzmann Stochastic Block Model: A Generative Model for Networks with Attributes. - Shubham Gupta; Ambedkar Dukkipati; Rui M. Castro (CoRR, 2019)

A Statistical Model for Dynamic Networks with Neural Variational Inference. - Shubham Gupta; Rui M. Castro; Ambedkar Dukkipati (CoRR, 2019)

Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs. - Tony Gracious; Shubham Gupta; Arun Kanthali; Rui M. Castro; Ambedkar Dukkipati (AAAI, 2021)

Equipping SBMs with RBMs: an interpretable approach for analysis of networks with covariates. - Shubham Gupta; Gururaj K; Ambedkar Dukkipati; Rui M. Castro (J. Complex Networks, 2021)

Adaptive Selective Sampling for Online Prediction with Experts. - Rui M. Castro; Fredrik Hellström; Tim van Erven (NeurIPS, 2023)