Showing 1–20 of 147 results
/ Date/ Name
Oct 16, 2011Regime Change: Bit-Depth versus Measurement-Rate in Compressive SensingMay 22, 2023Investigating the Role of Feed-Forward Networks in Transformers Using Parallel Attention and Feed-Forward Net DesignApr 26, 2011The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic RangeJan 31, 2009Beyond Nyquist: Efficient Sampling of Sparse Bandlimited SignalsFeb 25, 2024PIDformer: Transformer Meets Control TheoryOct 21, 2022Boomerang: Local sampling on image manifolds using diffusion modelsMar 7, 2022Singular Value Perturbation and Deep Network OptimizationNov 20, 2022Frozen Overparameterization: A Double Descent Perspective on Transfer Learning of Deep Neural NetworksDec 19, 2022MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource LanguagesDec 9, 2019InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive SolversJun 13, 2020Interpretable Super-Resolution via a Learned Time-Series RepresentationMay 22, 2019Thresholding Graph Bandits with GrAPLOct 15, 2021NeuroView: Explainable Deep Network Decision MakingFeb 16, 2017Insense: Incoherent Sensor Selection for Sparse SignalsNov 7, 2006Optimal sampling strategies for multiscale stochastic processesDec 6, 2016Semi-Supervised Learning with the Deep Rendering Mixture ModelSep 15, 2024Learning Transferable Features for Implicit Neural RepresentationsNov 4, 2024Estimating the Number and Locations of Boundaries in Reverberant Environments with Deep LearningNov 1, 2022TITAN: Bringing The Deep Image Prior to Implicit RepresentationsDec 19, 2014Estimating a Common Period for a Set of Irregularly Sampled Functions with Applications to Periodic Variable Star Data