Jonathan Mei

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 10

Top Topics

Latent Variable Models

Directed Acyclic

Stochastic Optimization

Top Venues

IEEE Trans. Signal Process.

Publications

Dominic Widdows, Willie Aboumrad, Dohun Kim, Sayonee Ray, Jonathan Mei
Natural Language, AI, and Quantum Computing in 2024: Research Ingredients and Directions in QNLP. CoRR (2024)
Jonathan Mei, Alexander Moreno, Luke Walters
KrADagrad: Kronecker approximation-domination gradient preconditioned stochastic optimization. UAI (2023)
Jonathan Mei, Alexander Moreno, Luke Walters
KrADagrad: Kronecker Approximation-Domination Gradient Preconditioned Stochastic Optimization. CoRR (2023)
Alexander Moreno, Jonathan Mei, Luke Walters
SKI to go Faster: Accelerating Toeplitz Neural Networks via Asymmetric Kernels. CoRR (2023)
Jonathan Mei, José M. F. Moura
Single Index Latent Variable Models for Network Topology Inference. CoRR (2018)
Jonathan Mei, José M. F. Moura
SILVar: Single Index Latent Variable Models. IEEE Trans. Signal Process. 66 (11) (2018)
Jonathan Mei, José M. F. Moura
Single Index Latent Variable Models for Network Topology Inference. GlobalSIP (2018)
Jonathan Mei, José M. F. Moura
EigenNetworks. CoRR (2018)
Jonathan Mei, José M. F. Moura
Signal Processing on Graphs: Causal Modeling of Unstructured Data. IEEE Trans. Signal Process. 65 (8) (2017)
Jonathan Mei, José M. F. Moura
Signal processing on graphs: Performance of graph structure estimation. ICASSP (2016)
Jonathan Mei, José M. F. Moura
Signal Processing on Graphs: Modeling (Causal) Relations in Big Data. CoRR (2015)
Jonathan Mei, José M. F. Moura
Signal processing on graphs: Estimating the structure of a graph. ICASSP (2015)
Jonathan Mei, José M. F. Moura
Fitting graph models to big data. ACSSC (2015)
Jonathan Mei, Ahmed Kirmani, Andrea Colaco, Vivek K. Goyal
Phase unwrapping and denoising for time-of-flight imaging using generalized approximate message passing. ICIP (2013)