b'Kevin Murphy'

research

∙ 05/31/2023

Low-rank extended Kalman filtering for online learning of neural networks from streaming data

We propose an efficient online approximate Bayesian inference algorithm ...

0 Peter Chang, et al. ∙

research

∙ 11/28/2022

Beyond Invariance: Test-Time Label-Shift Adaptation for Distributions with "Spurious" Correlations

Spurious correlations, or correlations that change across domains where ...

0 Qingyao Sun, et al. ∙

research

∙ 10/20/2022

Uncertainty Disentanglement with Non-stationary Heteroscedastic Gaussian Processes for Active Learning

Gaussian processes are Bayesian non-parametric models used in many areas...

0 Zeel B Patel, et al. ∙

research

∙ 07/21/2022

Language Model Cascades

Prompted models have demonstrated impressive few-shot learning abilities...

5 David Dohan, et al. ∙

research

∙ 03/07/2022

Hands-free Telelocomotion of a Wheeled Humanoid toward Dynamic Mobile Manipulation via Teleoperation

Robotic systems that can dynamically combine manipulation and locomotion...

0 Amartya Purushottam, et al. ∙

research

∙ 12/01/2021

Efficient Online Bayesian Inference for Neural Bandits

In this paper we present a new algorithm for online (sequential) inferen...

5 Gerardo Duran-Martin, et al. ∙

research

∙ 06/07/2021

Uncertainty Baselines: Benchmarks for Uncertainty Robustness in Deep Learning

High-quality estimates of uncertainty and robustness are crucial for num...

0 Zachary Nado, et al. ∙

research

∙ 04/17/2021

Risk score learning for COVID-19 contact tracing apps

Digital contact tracing apps for COVID-19, such as the one developed by ...

0 Kevin Murphy, et al. ∙

research

∙ 03/15/2021

HOPPY: An Open-source Kit for Education with Dynamic Legged Robots

This paper introduces HOPPY, an open-source, low-cost, robust, and modul...

0 Joao Ramos, et al. ∙

research

∙ 11/04/2020

A Comparison Between Joint Space and Task Space Mappings for Dynamic Teleoperation of an Anthropomorphic Robotic Arm in Reaction Tests

Teleoperation (i.e., controlling a robot with human motion) proves promi...

0 Sunyu Wang, et al. ∙

research

∙ 10/27/2020

HOPPY: An open-source and low-cost kit for dynamic robotics education

This letter introduces HOPPY, an open-source, low-cost, robust, and modu...

0 Joao Ramos, et al. ∙

research

∙ 06/05/2020

Population-Based Black-Box Optimization for Biological Sequence Design

The use of black-box optimization for the design of new biological seque...

1 Christof Angermueller, et al. ∙

research

∙ 05/07/2020

Machine Learning on Graphs: A Model and Comprehensive Taxonomy

There has been a surge of recent interest in learning representations fo...

44 Ines Chami, et al. ∙

research

∙ 04/24/2020

Towards Differentiable Resampling

Resampling is a key component of sample-based recursive state estimation...

6 Michael Zhu, et al. ∙

research

∙ 02/20/2020

Regularized Autoencoders via Relaxed Injective Probability Flow

Invertible flow-based generative models are an effective method for lear...

5 Abhishek Kumar, et al. ∙

research

∙ 12/13/2019

The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction

This paper studies the problem of predicting the distribution over multi...

32 Junwei Liang, et al. ∙

research

∙ 06/19/2019

Unsupervised Learning of Object Structure and Dynamics from Videos

Extracting and predicting object structure and dynamics from videos with...

4 Matthias Minderer, et al. ∙

research

∙ 06/18/2019

Language as an Abstraction for Hierarchical Deep Reinforcement Learning

Solving complex, temporally-extended tasks is a long-standing problem in...

9 Yiding Jiang, et al. ∙

research

∙ 06/16/2019

Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction

We propose 4 insights that help to significantly improve the performance...

4 Steven Hickson, et al. ∙

research

∙ 06/13/2019

Contrastive Bidirectional Transformer for Temporal Representation Learning

This paper aims at learning representations for long sequences of contin...

4 Chen Sun, et al. ∙

research

∙ 05/24/2019

A view of Estimation of Distribution Algorithms through the lens of Expectation-Maximization

We show that under mild conditions, Estimation of Distribution Algorithm...

0 David H. Brookes, et al. ∙

research

∙ 04/08/2019

Relational Action Forecasting

This paper focuses on multi-person action forecasting in videos. More pr...

16 Chen Sun, et al. ∙

research

∙ 04/03/2019

VideoBERT: A Joint Model for Video and Language Representation Learning

Self-supervised learning has become increasingly important to leverage t...

30 Chen Sun, et al. ∙

research

∙ 03/12/2019

Unsupervised Discovery of Parts, Structure, and Dynamics

Humans easily recognize object parts and their hierarchical structure by...

12 Zhenjia Xu, et al. ∙

research

∙ 02/25/2019

Stochastic Prediction of Multi-Agent Interactions from Partial Observations

We present a method that learns to integrate temporal information, from ...

8 Chen Sun, et al. ∙

research

∙ 02/25/2019

NAS-Bench-101: Towards Reproducible Neural Architecture Search

Recent advances in neural architecture search (NAS) demand tremendous co...

0 Chris Ying, et al. ∙

research

∙ 12/18/2018

Composing Text and Image for Image Retrieval - An Empirical Odyssey

In this paper, we study the task of image retrieval, where the input que...

21 Nam Vo, et al. ∙

research

∙ 09/30/2018

Modeling Uncertainty with Hedged Instance Embedding

Instance embeddings are an efficient and versatile image representation ...

0 Seong Joon Oh, et al. ∙

research

∙ 07/28/2018

Actor-Centric Relation Network

Current state-of-the-art approaches for spatio-temporal action localizat...

6 Chen Sun, et al. ∙

research

∙ 06/25/2018

Tracking Emerges by Colorizing Videos

We use large amounts of unlabeled video to learn models for visual track...

0 Carl Vondrick, et al. ∙

research

∙ 03/22/2018

PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model

We present a box-free bottom-up approach for the tasks of pose estimatio...

1 George Papandreou, et al. ∙

research

∙ 12/13/2017

Rethinking Spatiotemporal Feature Learning For Video Understanding

In this paper we study 3D convolutional networks for video understanding...

0 Saining Xie, et al. ∙

research

∙ 12/02/2017

Progressive Neural Architecture Search

We propose a method for learning CNN structures that is more efficient t...

0 Chenxi Liu, et al. ∙

research

∙ 11/14/2017

XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings

Style transfer usually refers to the task of applying color and texture ...

0 Amélie Royer, et al. ∙

research

∙ 11/01/2017

An Information-Theoretic Analysis of Deep Latent-Variable Models

We present an information-theoretic framework for understanding trade-of...

0 Alexander A. Alemi, et al. ∙

research

∙ 05/30/2017

Generative Models of Visually Grounded Imagination

It is easy for people to imagine what a man with pink hair looks like, e...

0 Ramakrishna Vedantam, et al. ∙

research

∙ 05/19/2017

PixColor: Pixel Recursive Colorization

We propose a novel approach to automatically produce multiple colorized ...

0 Sergio Guadarrama, et al. ∙

research

∙ 01/13/2017

Deep Probabilistic Programming

We propose Edward, a Turing-complete probabilistic programming language....

0 Dustin Tran, et al. ∙

research

∙ 01/11/2017

Context-aware Captions from Context-agnostic Supervision

We introduce an inference technique to produce discriminative context-aw...

0 Ramakrishna Vedantam, et al. ∙

research

∙ 01/06/2017

Towards Accurate Multi-person Pose Estimation in the Wild

We propose a method for multi-person detection and 2-D pose estimation t...

1 George Papandreou, et al. ∙

research

∙ 12/05/2016

Deep Metric Learning via Facility Location

Learning the representation and the similarity metric in an end-to-end f...

0 Hyun Oh Song, et al. ∙

research

∙ 12/01/2016

Improved Image Captioning via Policy Gradient optimization of SPIDEr

Current image captioning methods are usually trained via (penalized) max...

0 Siqi Liu, et al. ∙

research

∙ 11/30/2016

Speed/accuracy trade-offs for modern convolutional object detectors

The goal of this paper is to serve as a guide for selecting a detection ...

0 Jonathan Huang, et al. ∙

research

∙ 06/02/2016

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

In this work we address the task of semantic image segmentation with Dee...

0 Liang-Chieh Chen, et al. ∙

research

∙ 11/10/2015

Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform

Deep convolutional neural networks (CNNs) are the backbone of state-of-a...

0 Liang-Chieh Chen, et al. ∙

research

∙ 11/09/2015

Detecting events and key actors in multi-person videos

Multi-person event recognition is a challenging task, often with many pe...

0 Vignesh Ramanathan, et al. ∙

research

∙ 11/07/2015

Generation and Comprehension of Unambiguous Object Descriptions

We propose a method that can generate an unambiguous description (known ...

0 Junhua Mao, et al. ∙

research

∙ 09/08/2015

Nonlinear functional mapping of the human brain

The field of neuroimaging has truly become data rich, and novel analytic...

0 Nicholas Allgaier, et al. ∙

research

∙ 06/14/2015

Bayesian Dark Knowledge

We consider the problem of Bayesian parameter estimation for deep neural...

0 Anoop Korattikara, et al. ∙

research

∙ 03/05/2015

What's Cookin'? Interpreting Cooking Videos using Text, Speech and Vision

We present a novel method for aligning a sequence of instructions to a v...

0 Jonathan Malmaud, et al. ∙

Kevin Murphy

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