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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 ...
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11/28/2022
Beyond Invariance: Test-Time Label-Shift Adaptation for Distributions with "Spurious" Correlations
Spurious correlations, or correlations that change across domains where ...
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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...
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07/21/2022
Language Model Cascades
Prompted models have demonstrated impressive few-shot learning abilities...
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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...
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12/01/2021
Efficient Online Bayesian Inference for Neural Bandits
In this paper we present a new algorithm for online (sequential) inferen...
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06/07/2021
Uncertainty Baselines: Benchmarks for Uncertainty Robustness in Deep Learning
High-quality estimates of uncertainty and robustness are crucial for num...
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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 ...
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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...
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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...
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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...
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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...
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05/07/2020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
There has been a surge of recent interest in learning representations fo...
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04/24/2020
Towards Differentiable Resampling
Resampling is a key component of sample-based recursive state estimation...
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02/20/2020
Regularized Autoencoders via Relaxed Injective Probability Flow
Invertible flow-based generative models are an effective method for lear...
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12/13/2019
The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction
This paper studies the problem of predicting the distribution over multi...
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06/19/2019
Unsupervised Learning of Object Structure and Dynamics from Videos
Extracting and predicting object structure and dynamics from videos with...
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06/18/2019
Language as an Abstraction for Hierarchical Deep Reinforcement Learning
Solving complex, temporally-extended tasks is a long-standing problem in...
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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...
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06/13/2019
Contrastive Bidirectional Transformer for Temporal Representation Learning
This paper aims at learning representations for long sequences of contin...
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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...
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04/08/2019
Relational Action Forecasting
This paper focuses on multi-person action forecasting in videos. More pr...
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04/03/2019
VideoBERT: A Joint Model for Video and Language Representation Learning
Self-supervised learning has become increasingly important to leverage t...
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03/12/2019
Unsupervised Discovery of Parts, Structure, and Dynamics
Humans easily recognize object parts and their hierarchical structure by...
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02/25/2019
Stochastic Prediction of Multi-Agent Interactions from Partial Observations
We present a method that learns to integrate temporal information, from ...
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02/25/2019
NAS-Bench-101: Towards Reproducible Neural Architecture Search
Recent advances in neural architecture search (NAS) demand tremendous co...
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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...
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09/30/2018
Modeling Uncertainty with Hedged Instance Embedding
Instance embeddings are an efficient and versatile image representation ...
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07/28/2018
Actor-Centric Relation Network
Current state-of-the-art approaches for spatio-temporal action localizat...
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06/25/2018
Tracking Emerges by Colorizing Videos
We use large amounts of unlabeled video to learn models for visual track...
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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...
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12/13/2017
Rethinking Spatiotemporal Feature Learning For Video Understanding
In this paper we study 3D convolutional networks for video understanding...
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12/02/2017
Progressive Neural Architecture Search
We propose a method for learning CNN structures that is more efficient t...
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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 ...
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11/01/2017
An Information-Theoretic Analysis of Deep Latent-Variable Models
We present an information-theoretic framework for understanding trade-of...
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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...
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05/19/2017
PixColor: Pixel Recursive Colorization
We propose a novel approach to automatically produce multiple colorized ...
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01/13/2017
Deep Probabilistic Programming
We propose Edward, a Turing-complete probabilistic programming language....
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01/11/2017
Context-aware Captions from Context-agnostic Supervision
We introduce an inference technique to produce discriminative context-aw...
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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...
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12/05/2016
Deep Metric Learning via Facility Location
Learning the representation and the similarity metric in an end-to-end f...
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12/01/2016
Improved Image Captioning via Policy Gradient optimization of SPIDEr
Current image captioning methods are usually trained via (penalized) max...
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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 ...
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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...
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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...
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11/09/2015
Detecting events and key actors in multi-person videos
Multi-person event recognition is a challenging task, often with many pe...
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11/07/2015
Generation and Comprehension of Unambiguous Object Descriptions
We propose a method that can generate an unambiguous description (known ...
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09/08/2015
Nonlinear functional mapping of the human brain
The field of neuroimaging has truly become data rich, and novel analytic...
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06/14/2015
Bayesian Dark Knowledge
We consider the problem of Bayesian parameter estimation for deep neural...
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03/05/2015