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08/21/2023
Spectral Graphormer: Spectral Graph-based Transformer for Egocentric Two-Hand Reconstruction using Multi-View Color Images
We propose a novel transformer-based framework that reconstructs two hig...
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03/20/2023
Sandwiched Video Compression: Efficiently Extending the Reach of Standard Codecs with Neural Wrappers
We propose sandwiched video compression – a video compression system tha...
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12/25/2022
Exact Selective Inference with Randomization
We introduce a pivot for exact selective inference with randomization. N...
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07/14/2022
Developing a Series of AI Challenges for the United States Department of the Air Force
Through a series of federal initiatives and orders, the U.S. Government ...
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03/28/2022
Black-box Selective Inference via Bootstrapping
We propose a method for selective inference after a model selection proc...
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01/13/2022
VoLux-GAN: A Generative Model for 3D Face Synthesis with HDRI Relighting
We propose VoLux-GAN, a generative framework to synthesize 3D-aware face...
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05/18/2020
Deep Implicit Volume Compression
We describe a novel approach for compressing truncated signed distance f...
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03/14/2020
Inferring Treatment Effects After Testing Instrument Strength in Linear Models
A common practice in IV studies is to check for instrument strength, i.e...
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11/10/2019
Inference After Selecting Plausibly Valid Instruments with Application to Mendelian Randomization
Mendelian randomization (MR) is a popular method in genetic epidemiology...
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05/29/2019
Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learning
Volumetric (4D) performance capture is fundamental for AR/VR content gen...
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02/21/2019
Approximate selective inference via maximum likelihood
We consider an approximate version of the conditional approach to select...
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01/28/2019
Inference after black box selection
We consider the problem of inference for parameters selected to report o...
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11/12/2018
LookinGood: Enhancing Performance Capture with Real-time Neural Re-Rendering
Motivated by augmented and virtual reality applications such as telepres...
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08/07/2017
Why adaptively collected data have negative bias and how to correct for it
From scientific experiments to online A/B testing, the previously observ...
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12/02/2016
Summary - TerpreT: A Probabilistic Programming Language for Program Induction
We study machine learning formulations of inductive program synthesis; t...
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08/15/2016
TerpreT: A Probabilistic Programming Language for Program Induction
We study machine learning formulations of inductive program synthesis; g...
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07/22/2016
High-dimensional regression adjustments in randomized experiments
We study the problem of treatment effect estimation in randomized experi...
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12/08/2015
Selective Sequential Model Selection
Many model selection algorithms produce a path of fits specifying a sequ...
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05/22/2012
A lasso for hierarchical interactions
We add a set of convex constraints to the lasso to produce sparse intera...
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02/15/2011
A Generalized Least Squares Matrix Decomposition
Variables in many massive high-dimensional data sets are structured, ari...
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11/09/2010