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Behtash Babadi
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2020 – today
- 2024
- [j30]Shoutik Mukherjee
, Behtash Babadi
Adaptive modeling and inference of higher-order coordination in neuronal assemblies: A dynamic greedy estimation approach. PLoS Comput. Biol. 20(5): 1011605 (2024) - [c38]Shoutik Mukherjee, Peter Jendrichovksy, Patrick O. Kanold, Behtash Babadi:
Reinforcement Learning-Guided Optogenetic Stimulation Policies for Robust Functional Network Discovery. ICASSP 2024: 13271-13275 - 2023
- [j29]Loren Koçillari, Marco Celotto, Nikolas A. Francis, Shoutik Mukherjee, Behtash Babadi, Patrick O. Kanold, Stefano Panzeri:
Behavioural relevance of redundant and synergistic stimulus information between functionally connected neurons in mouse auditory cortex. Brain Informatics 10(1): 34 (2023) - [j28]Proloy Das
Non-Asymptotic Guarantees for Reliable Identification of Granger Causality via the LASSO. IEEE Trans. Inf. Theory 69(11): 7439-7460 (2023) - [c37]Ruwanthi Abeysekara, Christopher J. Smalt, I. M. Dushyanthi Karunathilake, Jonathan Z. Simon, Behtash Babadi:
Information-Theoretic Limits on the Performance of Auditory Attention Decoders. ACSSC 2023: 1479-1483 - [c36]Loren Koçillari
Measuring Stimulus-Related Redundant and Synergistic Functional Connectivity with Single Cell Resolution in Auditory Cortex. BI 2023: 45-56 - 2022
- [j27]Behrad Soleimani, Proloy Das
NLGC: Network localized Granger causality with application to MEG directional functional connectivity analysis. NeuroImage 260: 119496 (2022) - [c35]Sahar Khosravi, Anuththara Rupasinghe
Granger Causal Inference from Spiking Observations via Latent Variable Modeling. IEEECONF 2022: 618-622 - 2021
- [c34]Shoutik Mukherjee, Behtash Babadi:
Dynamic Analysis of Higher-Order Coordination in Neuronal Assemblies via De-Sparsified Orthogonal Matching Pursuit. NeurIPS 2021: 4120-4133 - [i11]Proloy Das, Behtash Babadi:
Non-Asymptotic Guarantees for Robust Identification of Granger Causality via the LASSO. CoRR abs/2103.02774 (2021) - 2020
- [j26]Proloy Das, Christian Brodbeck
Neuro-current response functions: A unified approach to MEG source analysis under the continuous stimuli paradigm. NeuroImage 211: 116528 (2020) - [j25]Sina Miran, Alessandro Presacco, Jonathan Z. Simon
Dynamic estimation of auditory temporal response functions via state-space models with Gaussian mixture process noise. PLoS Comput. Biol. 16(8) (2020) - [j24]Proloy Das
Multitaper spectral analysis of neuronal spiking activity driven by latent stationary processes. Signal Process. 170: 107429 (2020) - [j23]Anuththara Rupasinghe
Multitaper Analysis of Semi-Stationary Spectra From Multivariate Neuronal Spiking Observations. IEEE Trans. Signal Process. 68: 4382-4396 (2020) - [c33]Anuththara Rupasinghe
Adaptive Frequency-domain Granger Causal Inference from Neuronal Ensemble Data. ACSSC 2020: 101-105 - [c32]Anuththara Rupasinghe
Robust Inference of Neuronal Correlations from Blurred and Noisy Spiking Observations. CISS 2020: 1-5 - [c31]Behrad Soleimani, Proloy Das, Joshua Kulasingham
Granger Causal Inference from Indirect Low-Dimensional Measurements with Application to MEG Functional Connectivity Analysis. CISS 2020: 1-5
2010 – 2019
- 2019
- [c30]Shoutik Mukherjee, Behtash Babadi:
A Statistical Approach to Dynamic Synchrony Analysis of Neuronal Ensemble Spiking. ACSSC 2019: 1719-1723 - [c29]Anuththara Rupasinghe
Multitaper Analysis of Evolutionary Spectral Density Matrix From Multivariate Spiking Observations. DSW 2019: 47-51 - [c28]Sina Miran, Jonathan Z. Simon, Michael C. Fu, Steven I. Marcus, Behtash Babadi:
Estimation of State-Space Models with Gaussian Mixture Process Noise. DSW 2019: 185-189 - [c27]Alessandro Presacco, Sina Miran, Behtash Babadi, Jonathan Z. Simon:
Real-Time Tracking of Magnetoencephalographic Neuromarkers during a Dynamic Attention-Switching Task. EMBC 2019: 4148-4151 - [i10]Proloy Das, Behtash Babadi:
Multitaper Spectral Analysis of Neuronal Spiking Activity Driven by Latent Stationary Processes. CoRR abs/1906.08451 (2019) - [i9]Anuththara Rupasinghe, Behtash Babadi:
Multitaper Analysis of Evolutionary Spectra from Multivariate Spiking Observations. CoRR abs/1906.09359 (2019) - 2018
- [j22]Abbas Kazemipour, Ji Liu, Krystyna Solarana
Fast and Stable Signal Deconvolution via Compressible State-Space Models. IEEE Trans. Biomed. Eng. 65(1): 74-86 (2018) - [j21]Elvira Pirondini
Computationally Efficient Algorithms for Sparse, Dynamic Solutions to the EEG Source Localization Problem. IEEE Trans. Biomed. Eng. 65(6): 1359-1372 (2018) - [j20]Proloy Das
Dynamic Bayesian Multitaper Spectral Analysis. IEEE Trans. Signal Process. 66(6): 1394-1409 (2018) - [c26]Proloy Das
Cortical Localization of the Auditory Temporal Response Function from MEG via Non-convex Optimization. ACSSC 2018: 373-378 - [c25]Sina Miran, Sahar Akram, Alireza Sheikhattar, Jonathan Z. Simon, Tao Zhang, Behtash Babadi:
Real-Time Decoding of Auditory Attention from EEG via Bayesian Filtering. EMBC 2018: 25-28 - 2017
- [j19]Sahar Akram, Jonathan Z. Simon
Dynamic Estimation of the Auditory Temporal Response Function From MEG in Competing-Speaker Environments. IEEE Trans. Biomed. Eng. 64(8): 1896-1905 (2017) - [j18]Sina Miran, Patrick L. Purdon, Emery N. Brown, Behtash Babadi:
Robust Estimation of Sparse Narrowband Spectra from Neuronal Spiking Data. IEEE Trans. Biomed. Eng. 64(10): 2462-2474 (2017) - [j17]Abbas Kazemipour, Sina Miran, Piya Pal, Behtash Babadi, Min Wu
Sampling Requirements for Stable Autoregressive Estimation. IEEE Trans. Signal Process. 65(9): 2333-2347 (2017) - [j16]Abbas Kazemipour, Min Wu
Robust Estimation of Self-Exciting Generalized Linear Models With Application to Neuronal Modeling. IEEE Trans. Signal Process. 65(14): 3733-3748 (2017) - [j15]Rémy Boyer, Behtash Babadi, Nicholas Kalouptsidis, Vahid Tarokh:
Corrections to "Asymptotic Achievability of the Cramér-Rao Bound for Noisy Compressive Sampling". IEEE Trans. Signal Process. 65(18): 4973-4974 (2017) - [c24]Pavitra Krishnaswamy, Gabriel Obregon-Henao, Sheraz Khan, Behtash Babadi, Eugenio Iglesias, Matti S. Hämäläinen, Patrick L. Purdon:
Sparse Representation Learning Approach Resolves Deep Sources Underlying MEG and EEG Data. AAAI Spring Symposia 2017 - [c23]Alireza Sheikhattar, Siamak K. Sorooshyari
An autoregressive approach to inference in populations of correlated stochastic neurons. ACSSC 2017: 2020-2024 - [c22]Abbas Kazemipour, Behtash Babadi, Min Wu, Kaspar Podgorski
Multiplicative updates for optimization problems with dynamics. ACSSC 2017: 2025-2029 - [c21]Sina Miran, Patrick L. Purdon, Emery N. Brown, Behtash Babadi:
Sparse spectral estimation from point process observations. ICASSP 2017: 841-845 - [i8]Proloy Das, Behtash Babadi:
Dynamic Bayesian Multitaper Spectral Analysis. CoRR abs/1706.01563 (2017) - 2016
- [j14]Sahar Akram, Alessandro Presacco, Jonathan Z. Simon
Robust decoding of selective auditory attention from MEG in a competing-speaker environment via state-space modeling. NeuroImage 124: 906-917 (2016) - [j13]Alireza Sheikhattar, Jonathan B. Fritz
Recursive Sparse Point Process Regression With Application to Spectrotemporal Receptive Field Plasticity Analysis. IEEE Trans. Signal Process. 64(8): 2026-2039 (2016) - [c20]Alireza Sheikhattar, Sina Miran, Jonathan B. Fritz
Probing the functional circuitry underlying auditory attention via dynamic granger causality analysis. ACSSC 2016: 593-597 - [c19]Abbas Kazemipour, Behtash Babadi, Min Wu:
Sufficient conditions for stable recovery of sparse autoregressive models. CISS 2016: 396-400 - [c18]Alireza Sheikhattar, Behtash Babadi:
Dynamic estimation of causal influences in sparsely-interacting neuronal ensembles. CISS 2016: 551-556 - [c17]Alireza Sheikhattar, Behtash Babadi:
Real-time Algorithms for Sparse Neuronal System Identification. EMBC 2016: 3410-3413 - [c16]Abbas Kazemipour, Ji Liu, Patrick O. Kanold, Min Wu, Behtash Babadi:
Efficient estimation of compressible state-space models with application to calcium signal deconvolution. GlobalSIP 2016: 1176-1180 - [i7]Abbas Kazemipour, Sina Miran, Piya Pal, Behtash Babadi, Min Wu:
Sampling Requirements for Stable Autoregressive Estimation. CoRR abs/1605.01436 (2016) - [i6]Abbas Kazemipour, Ji Liu, Patrick O. Kanold, Min Wu, Behtash Babadi:
Efficient Estimation of Compressible State-Space Models with Application to Calcium Signal Deconvolution. CoRR abs/1610.06461 (2016) - 2015
- [c15]Alireza Sheikhattar, Jonathan B. Fritz
Adaptive sparse logistic regression with application to neuronal plasticity analysis. ACSSC 2015: 1551-1555 - [i5]Abbas Kazemipour, Min Wu, Behtash Babadi:
Robust Estimation of Self-Exciting Point Process Models with Application to Neuronal Modeling. CoRR abs/1507.03955 (2015) - [i4]Alireza Sheikhattar, Jonathan B. Fritz, Shihab A. Shamma, Behtash Babadi:
Recursive Sparse Point Process Regression with Application to Spectrotemporal Receptive Field Plasticity Analysis. CoRR abs/1507.04727 (2015) - [i3]Behtash Babadi, Nicholas Kalouptsidis, Vahid Tarokh:
Comment on "Asymptotic Achievability of the Cramér-Rao Bound for Noisy Compressive Sampling". CoRR abs/1509.04375 (2015) - 2014
- [j12]Behtash Babadi, Gabriel Obregon-Henao
A Subspace Pursuit-based Iterative Greedy Hierarchical solution to the neuromagnetic inverse problem. NeuroImage 87: 427-443 (2014) - [j11]Behtash Babadi, Emery N. Brown:
A Review of Multitaper Spectral Analysis. IEEE Trans. Biomed. Eng. 61(5): 1555-1564 (2014) - [j10]Demba E. Ba, Behtash Babadi, Patrick L. Purdon, Emery N. Brown:
Convergence and Stability of Iteratively Re-weighted Least Squares Algorithms. IEEE Trans. Signal Process. 62(1): 183-195 (2014) - [c14]Demba E. Ba, Behtash Babadi, Patrick L. Purdon, Emery N. Brown:
Neural spike train denoising by point process re-weighted iterative smoothing. ACSSC 2014: 763-768 - [c13]Abbas Kazemipour, Behtash Babadi, Min Wu:
Sparse estimation of self-exciting point processes with application to LGN neural modeling. GlobalSIP 2014: 478-482 - [c12]Sahar Akram, Jonathan Z. Simon, Shihab A. Shamma, Behtash Babadi:
A State-Space Model for Decoding Auditory Attentional Modulation from MEG in a Competing-Speaker Environment. NIPS 2014: 460-468 - 2013
- [j9]Behtash Babadi, Vahid Tarokh:
Spectral Distribution of Product of Pseudorandom Matrices Formed From Binary Block Codes. IEEE Trans. Inf. Theory 59(2): 970-978 (2013) - 2012
- [j8]Behtash Babadi, Vahid Tarokh:
Distributed Dynamic Spectrum Allocation for Secondary Users in a Vertical Spectrum Sharing Scenario. IEICE Trans. Commun. 95-B(4): 1044-1055 (2012) - [j7]Behtash Babadi, Scott M. McKinney, Vahid Tarokh, Jeffrey M. Ellenbogen:
DiBa: A Data-Driven Bayesian Algorithm for Sleep Spindle Detection. IEEE Trans. Biomed. Eng. 59(2): 483-493 (2012) - [c11]Behtash Babadi, Vahid Tarokh:
Vertical spectrum sharing via distributed asynchronous interference avoidance in cognitive radio networks. CCNC 2012: 869-873 - [c10]Aaron L. Sampson, Behtash Babadi, Michael J. Prerau
Beamforming approach to phase-amplitude modulation analysis of multi-channel EEG. EMBC 2012: 6731-6734 - [c9]Gabriel Obregon-Henao
A fast iterative greedy algorithm for MEG source localization. EMBC 2012: 6748-6751 - [c8]Elvira Pirondini, Behtash Babadi, Camilo Lamus, Emery N. Brown, Patrick L. Purdon:
A spatially-regularized dynamic source localization algorithm for EEG. EMBC 2012: 6752-6755 - [c7]Demba E. Ba, Behtash Babadi, Patrick L. Purdon, Emery N. Brown:
Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization. NIPS 2012: 2636-2644 - 2011
- [j6]Nicholas Kalouptsidis, Gerasimos Mileounis, Behtash Babadi, Vahid Tarokh:
Adaptive algorithms for sparse system identification. Signal Process. 91(8): 1910-1919 (2011) - [j5]Behtash Babadi, Vahid Tarokh:
Spectral Distribution of Random Matrices From Binary Linear Block Codes. IEEE Trans. Inf. Theory 57(6): 3955-3962 (2011) - [c6]Behtash Babadi, Vahid Tarokh:
Spectral distribution of the product of two random matrices based on binary block codes. Allerton 2011: 917-919 - [c5]Gerasimos Mileounis, Nicholas Kalouptsidis, Behtash Babadi, Vahid Tarokh:
Blind identification of sparse channels and symbol detection via the EM algorithm. DSP 2011: 1-5 - [c4]Behtash Babadi, Vahid Tarokh:
Regularized recursive least squares for anomaly detection in sparse channel tracking applications. RACS 2011: 277-281 - 2010
- [j4]Behtash Babadi, Vahid Tarokh:
GADIA: A Greedy Asynchronous Distributed Interference Avoidance Algorithm. IEEE Trans. Inf. Theory 56(12): 6228-6252 (2010) - [j3]Gerasimos Mileounis, Behtash Babadi, Nicholas Kalouptsidis, Vahid Tarokh:
An adaptive greedy algorithm with application to nonlinear communications. IEEE Trans. Signal Process. 58(6): 2998-3007 (2010) - [j2]Behtash Babadi, Nicholas Kalouptsidis, Vahid Tarokh:
SPARLS: the sparse RLS algorithm. IEEE Trans. Signal Process. 58(8): 4013-4025 (2010) - [c3]Behtash Babadi, Vahid Tarokh:
Random frames from binary linear block codes. CISS 2010: 1-3 - [c2]Gerasimos Mileounis, Behtash Babadi, Nicholas Kalouptsidis, Vahid Tarokh:
An Adaptive Greedy Algorithm with Application to Sparse Narma Identification. ICASSP 2010: 3810-3813
2000 – 2009
- 2009
- [j1]Behtash Babadi, Nicholas Kalouptsidis, Vahid Tarokh:
Asymptotic Achievability of the CramÉr-Rao Bound for Noisy Compressive Sampling. IEEE Trans. Signal Process. 57(3): 1233-1236 (2009) - [i2]Behtash Babadi, Nicholas Kalouptsidis, Vahid Tarokh:
SPARLS: A Low Complexity Recursive $\mathcal{L}_1$-Regularized Least Squares Algorithm. CoRR abs/0901.0734 (2009) - 2008
- [c1]Behtash Babadi, Vahid Tarokh:
A distributed asynchronous algorithm for spectrum sharing in wireless ad hoc networks. CISS 2008: 831-835 - 2007
- [i1]Behtash Babadi, Vahid Tarokh:
A Distributed Dynamic Frequency Allocation Algorithm For Ad Hoc Networks. CoRR abs/0711.3247 (2007)
Coauthor Index
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last updated on 2024-12-02 22:28 CET by the dblp team
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