Badrinath Roysam

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All published works

Action	Title	Year	Authors
+	Few Is Enough: Task-Augmented Active Meta-Learning for Brain Cell Classification	2020	Pengyu Yuan Aryan Mobiny Jahandar Jahanipour Xiaoyang Li Pietro Antonio Cicalese Badrinath Roysam Vishal M. Patel Maric Dragan Hien Van Nguyen
+ PDF Chat	Few Is Enough: Task-Augmented Active Meta-learning for Brain Cell Classification	2020	Pengyu Yuan Aryan Mobiny Jahandar Jahanipour Xiaoyang Li Pietro Antonio Cicalese Badrinath Roysam Vishal M. Patel Maric Dragan Hien Van Nguyen
+ PDF Chat	An Active Learning Approach for Rapid Characterization of Endothelial Cells in Human Tumors	2014	Raghav Padmanabhan Vinay H. Somasundar Sandra D. Griffith Jianliang Zhu Drew Samoyedny Kay See Tan Jiahao Hu Xuejun Liao Lawrence Carin Sam S. Yoon
+ PDF Chat	Image Variational Denoising Using Gradient Fidelity on Curvelet Shrinkage	2010	Liang Xiao Lili Huang Badrinath Roysam
+	Robust 3-D Modeling of Tumor Microvasculature Using Superellipsoids	2006	James Tyrrell Badrinath Roysam Emmanuelle di Tomaso R. Tong Edward B. Brown R K Jain
+	Automated in vivo change analysis of tumor vasculature from two-photon confocal image time series	2003	Muhammad‐Amri Abdul‐Karim Omar Al-Kofahi Edward B. Brown Rakesh K. Jain Khalid Al-Kofahi Badrinath Roysam
+	A unified approach for hierarchical imaging based on joint hypothesis testing and parameter estimation	2003	Badrinath Roysam Michael I. Miller
+	Bayesian imaging using Good's roughness measure-implementation on a massively parallel processor	2003	Badrinath Roysam J.A. Shrauner Michael I. Miller
+	Going Beyond 3-D Imaging: Automated 3-D Montaged image Analysis of Cytological Specimens	1996	Badrinath Roysam Hakan Ancin Douglas E. Becker Robert W. Mackin Matthew M. Chestnut Gregg M. Ridder Thomas E. Dufresne Donald H. Szarowski James N. Turner
+ PDF Chat	Bayesian image reconstruction for emission tomography incorporating Good's roughness prior on massively parallel processors.	1991	Michael I. Miller Badrinath Roysam

Common Coauthors

Coauthor	Papers Together
Michael I. Miller	3
Jahandar Jahanipour	2
Xiaoyang Li	2
Vishal M. Patel	2
Hien Van Nguyen	2
Edward B. Brown	2
Pengyu Yuan	2
Aryan Mobiny	2
Pietro Antonio Cicalese	2
Maric Dragan	2
Sam S. Yoon	1
Michael D. Feldman	1
Matthew M. Chestnut	1
Omar Al-Kofahi	1
R K Jain	1
Hakan Ancin	1
James N. Turner	1
J.A. Shrauner	1
Kay See Tan	1
Drew Samoyedny	1
William M. F. Lee	1
Jiahao Hu	1
Priti Lal	1
Lili Huang	1
Robert S. DiPaola	1
Muhammad‐Amri Abdul‐Karim	1
Donald H. Szarowski	1
Raghav Padmanabhan	1
Jianliang Zhu	1
Gregg M. Ridder	1
Xuejun Liao	1
R. Tong	1
Thomas E. Dufresne	1
Sandra D. Griffith	1
James Tyrrell	1
Douglas E. Becker	1
Vinay H. Somasundar	1
Khalid Al-Kofahi	1
Rakesh K. Jain	1
Lawrence Carin	1
Emmanuelle di Tomaso	1
Liang Xiao	1
Keith T. Flaherty	1
Robert W. Mackin	1
Daniel F. Heitjan	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	2015	Yarin Gal Zoubin Ghahramani	2
+	Prototypical Networks for Few-shot Learning	2017	Jake Snell Kevin Swersky Richard S. Zemel	2
+	Non-parametric Roughness Penalty for Probability Densities	1971	I. J. Good	2
+	One-shot Learning with Memory-Augmented Neural Networks	2016	Adam Santoro Sergey Bartunov Matthew Botvinick Daan Wierstra Timothy Lillicrap	2
+	Learning to learn by gradient descent by gradient descent	2016	Marcin Andrychowicz Misha Denil Sergio Luis Suárez Gómez Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas	2
+	A MULTISCALE WAVELET-INSPIRED SCHEME FOR NONLINEAR DIFFUSION	2006	Gerlind Plonka Gabriele Steidl	1
+	Nonstationary Markov chains and convergence of the annealing algorithm	1985	Basilis Gidas	1
+	New tight frames of curvelets and optimal representations of objects with piecewise <i>C</i><sup>2</sup> singularities	2003	Emmanuel J. Candès David L. Donoho	1
+ PDF Chat	The Probable Error of a Mean	1908	Student	1
+ PDF Chat	Nonparametric Maximum Likelihood Estimation of Probability Densities by Penalty Function Methods	1975	G. F. de Montricher R. A. Tapia James R. Thompson	1
+	The role of likelihood and entropy in incomplete-data problems: Applications to estimating point-process intensities and toeplitz constrained covariances	1987	Michael I. Miller Donald L. Snyder	1
+	Stereology of arbitrary particles. A review of unbiased number and size estimators and the presentation of some new ones, in memory of William R. Thompson.	1986	H. J. G. Gundersen	1
+	Semi-supervised Learning with Deep Generative Models	2014	Diederik P. Kingma Shakir Mohamed Danilo Jimenez Rezende Max Welling	1
+	EfficientL 1 regularized logistic regression	2006	Sun-In Lee Honglak Lee Pieter Abbeel Andrew Y. Ng	1
+ PDF Chat	Image Selective Smoothing and Edge Detection by Nonlinear Diffusion. II	1992	Luis Álvarez Pierre-Louis Lions Jean‐Michel Morel	1
+	Ideal spatial adaptation by wavelet shrinkage	1994	David L. Donoho Iain M. Johnstone	1
+	Bayesian imaging using Good's roughness measure-implementation on a massively parallel processor	2003	Badrinath Roysam J.A. Shrauner Michael I. Miller	1
+	Matching Networks for One Shot Learning	2016	Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra	1
+	Active One-shot Learning	2017	Mark P. Woodward Chelsea Finn	1
+	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	2017	Chelsea Finn Pieter Abbeel Sergey Levine	1
+	Learning how to Active Learn: A Deep Reinforcement Learning Approach	2017	Meng Fang Yuan Li Trevor Cohn	1
+	Understanding Measures of Uncertainty for Adversarial Example Detection	2018	Lewis Smith Yarin Gal	1
+	Semi-Supervised Learning with Deep Generative Models	2014	Diederik P. Kingma Danilo Jimenez Rezende Shakir Mohamed Max Welling	1
+	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	2017	Chelsea Finn Pieter Abbeel Sergey Levine	1
+	Deep Bayesian Active Learning with Image Data	2017	Yarin Gal Riashat Islam Zoubin Ghahramani	1
+	Matching networks for one shot learning	2016	Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra	1
+ PDF Chat	Learning how to Active Learn: A Deep Reinforcement Learning Approach	2017	Meng Fang Yuan Li Trevor Cohn	1
+	Information Theory and Statistics	2011	Evgueni Haroutunian	1
+	Nonparametric Roughness Penalties for Probability Densities	1971	I. J. Good R. A. Gaskins	1
+	Stereology of arbitrary particles*	1986	H. J. G. Gundersen	1
+ PDF Chat	Elliptic Partial Differential Equations of Second Order	2001	David Gilbarg Neil S. Trudinger	1
+	Information Theory and Statistics	2005	Thomas M. Cover Joy A. Thomas	1
+	None	1999	Pierre Kornprobst Rachid Deriche Gilles Aubert	1
+	Denoising of Frame Coefficients Using $\ell^1$ Data-Fidelity Term and Edge-Preserving Regularization	2007	Sylvain Durand Mila Nikolova	1
+	Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images	1984	Stuart Geman Donald Geman	1
+	Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm	1977	A. P. Dempster N. M. Laird Donald B. Rubin	1