The University of British Columbia

research

∙ 10/28/2021

From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence

Machine learning has long since become a keystone technology, accelerati...

Nicholas Roy, et al. ∙

research

∙ 05/22/2019

AttentionRNN: A Structured Spatial Attention Mechanism

Visual attention mechanisms have proven to be integrally important const...

Siddhesh Khandelwal, et al. ∙

research

∙ 04/07/2022

Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients

Supervised federated learning (FL) enables multiple clients to share the...

Nan Lu, et al. ∙

research

∙ 02/26/2019

AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks

Recurrent neural networks have gained widespread use in modeling sequent...

Bo Chang, et al. ∙

research

∙ 03/12/2022

Evaluating Explainable AI on a Multi-Modal Medical Imaging Task: Can Existing Algorithms Fulfill Clinical Requirements?

Being able to explain the prediction to clinical end-users is a necessit...

Weina Jin, et al. ∙

research

∙ 12/19/2021

FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction

Graph Convolutional Neural Networks (GCNs) are widely used for graph ana...

Liang Peng, et al. ∙

research

∙ 11/26/2019

A Preliminary Study of Disentanglement With Insights on the Inadequacy of Metrics

Disentangled encoding is an important step towards a better representati...

Amir H. Abdi, et al. ∙

research

∙ 12/07/2018

Building Ethics into Artificial Intelligence

As artificial intelligence (AI) systems become increasingly ubiquitous, ...

Han Yu, et al. ∙

research

∙ 01/17/2022

Learning Wave Propagation with Attention-Based Convolutional Recurrent Autoencoder Net

In this paper, we present an end-to-end attention-based convolutional re...

Indu Kant Deo, et al. ∙

research

∙ 03/15/2022

SemiPFL: Personalized Semi-Supervised Federated Learning Framework for Edge Intelligence

Recent advances in wearable devices and Internet-of-Things (IoT) have le...

Arvin Tashakori, et al. ∙

research

∙ 03/12/2019

Imitation Learning of Factored Multi-agent Reactive Models

We apply recent advances in deep generative modeling to the task of imit...

Michael Teng, et al. ∙

research

∙ 01/25/2020

The role of surrogate models in the development of digital twins of dynamic systems

Digital twin technology has significant promise, relevance and potential...

Souvik Chakraborty, et al. ∙

research

∙ 09/08/2021

EMA: Auditing Data Removal from Trained Models

Data auditing is a process to verify whether certain data have been remo...

Yangsibo Huang, et al. ∙

research

∙ 02/14/2022

Regional Differences in Information Privacy Concerns After the Facebook-Cambridge Analytica Data Scandal

While there is increasing global attention to data privacy, most of thei...

Felipe González-Pizarro, et al. ∙

research

∙ 02/16/2022

Guidelines and evaluation for clinical explainable AI on medical image analysis

Explainable artificial intelligence (XAI) is essential for enabling clin...

Weina Jin, et al. ∙

research

∙ 05/27/2022

Group GAN

Generating multivariate time series is a promising approach for sharing ...

Ali Seyfi, et al. ∙

research

∙ 05/24/2019

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates

Recent works have shown that stochastic gradient descent (SGD) achieves ...

Sharan Vaswani, et al. ∙

research

∙ 03/17/2022

GATE: Graph CCA for Temporal SElf-supervised Learning for Label-efficient fMRI Analysis

In this work, we focus on the challenging task, neuro-disease classifica...

Liang Peng, et al. ∙

research

∙ 08/12/2021

A Contract Theory based Incentive Mechanism for Federated Learning

Federated learning (FL) serves as a data privacy-preserved machine learn...

Mengmeng Tian, et al. ∙

research

∙ 03/18/2019

Neural Sequential Phrase Grounding (SeqGROUND)

We propose an end-to-end approach for phrase grounding in images. Unlike...

Pelin Dogan, et al. ∙

research

∙ 06/19/2020

Valid Causal Inference with (Some) Invalid Instruments

Instrumental variable methods provide a powerful approach to estimating ...

Jason Hartford, et al. ∙

research

∙ 09/16/2021

ROS-X-Habitat: Bridging the ROS Ecosystem with Embodied AI

We introduce ROS-X-Habitat, a software interface that bridges the AI Hab...

Guanxiong Chen, et al. ∙

research

∙ 04/12/2022

Convolutional recurrent autoencoder network for learning underwater ocean acoustics

Underwater ocean acoustics is a complex physical phenomenon involving no...

Wrik Mallik, et al. ∙

research

∙ 04/14/2022

Sign Bit is Enough: A Learning Synchronization Framework for Multi-hop All-reduce with Ultimate Compression

Traditional one-bit compressed stochastic gradient descent can not be di...

Feijie Wu, et al. ∙

research

∙ 03/21/2020

Smarter Parking: Using AI to Identify Parking Inefficiencies in Vancouver

On-street parking is convenient, but has many disadvantages: on-street s...

Devon Graham, et al. ∙

research

∙ 04/07/2021

Distilling and Transferring Knowledge via cGAN-generated Samples for Image Classification and Regression

Knowledge distillation (KD) has been actively studied for image classifi...

Xin Ding, et al. ∙

research

∙ 09/08/2018

Learning Sports Camera Selection from Internet Videos

This work addresses camera selection, the task of predicting which camer...

Jianhui Chen, et al. ∙

research

∙ 11/30/2018

Instance-level Facial Attributes Transfer with Geometry-Aware Flow

We address the problem of instance-level facial attribute transfer witho...

Weidong Yin, et al. ∙

research

∙ 02/05/2020

CHAIN: Concept-harmonized Hierarchical Inference Interpretation of Deep Convolutional Neural Networks

With the great success of networks, it witnesses the increasing demand f...

Dan Wang, et al. ∙

research

∙ 03/28/2020

Coping With Simulators That Don't Always Return

Deterministic models are approximations of reality that are easy to inte...

Andrew Warrington, et al. ∙

research

∙ 05/16/2020

Learning Joint Articulatory-Acoustic Representations with Normalizing Flows

The articulatory geometric configurations of the vocal tract and the aco...

Pramit Saha, et al. ∙

research

∙ 11/27/2020

PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers

Local processing is an essential feature of CNNs and other neural networ...

Frank Yu, et al. ∙

research

∙ 09/24/2021

On the Fairness of Swarm Learning in Skin Lesion Classification

in healthcare. However, the existing AI model may be biased in its decis...

Di Fan, et al. ∙

research

∙ 05/16/2019

Efficient Deep Gaussian Process Models for Variable-Sized Input

Deep Gaussian processes (DGP) have appealing Bayesian properties, can ha...

Issam H. Laradji, et al. ∙

research

∙ 04/15/2020

Joint User Pairing and Association for Multicell NOMA: A Pointer Network-based Approach

In this paper, we investigate the joint user pairing and association pro...

Manyou Ma, et al. ∙

research

∙ 06/29/2020

Ultra2Speech – A Deep Learning Framework for Formant Frequency Estimation and Tracking from Ultrasound Tongue Images

Thousands of individuals need surgical removal of their larynx due to cr...

Pramit Saha, et al. ∙

research

∙ 08/28/2020

Hierarchical Marketing Mix Models with Sign Constraints

Marketing mix models (MMMs) are statistical models for measuring the eff...

Hao Chen, et al. ∙

research

∙ 05/25/2022

Formalizing Preferences Over Runtime Distributions

When trying to solve a computational problem we are often faced with a c...

Devon R Graham, et al. ∙

research

∙ 07/20/2018

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model

We present a novel framework that enables efficient probabilistic infere...

Atilim Gunes Baydin, et al. ∙

research

∙ 09/13/2018

Does Your Model Know the Digit 6 Is Not a Cat? A Less Biased Evaluation of "Outlier" Detectors

In the real world, a learning system could receive an input that looks n...

Alireza Shafaei, et al. ∙

research

∙ 07/24/2019

LayoutVAE: Stochastic Scene Layout Generation from a Label Set

Recently there is an increasing interest in scene generation within the ...

Akash Abdu Jyothi, et al. ∙

research

∙ 06/08/2022

Hypernetwork-based Personalized Federated Learning for Multi-Institutional CT Imaging

Computed tomography (CT) is of great importance in clinical practice due...

Ziyuan Yang, et al. ∙

research

∙ 06/25/2018

Inference Trees: Adaptive Inference with Exploration

We introduce inference trees (ITs), a new class of inference methods tha...

Tom Rainforth, et al. ∙

research

∙ 07/25/2018

Where are the Blobs: Counting by Localization with Point Supervision

Object counting is an important task in computer vision due to its growi...

Issam H. Laradji, et al. ∙

research

∙ 09/27/2018

An Introduction to Probabilistic Programming

This document is designed to be a first-year graduate-level introduction...

Jan-Willem van de Meent, et al. ∙

research

∙ 06/14/2019

Instance Segmentation with Point Supervision

Instance segmentation methods often require costly per-pixel labels. We ...

Issam H. Laradji, et al. ∙

research

∙ 10/03/2020

Assisting the Adversary to Improve GAN Training

We propose a method for improved training of generative adversarial netw...

Andreas Munk, et al. ∙

research

∙ 02/28/2022

Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment

Maintaining proper form while exercising is important for preventing inj...

Paritosh Parmar, et al. ∙

research

∙ 03/23/2022

NeuMan: Neural Human Radiance Field from a Single Video

Photorealistic rendering and reposing of humans is important for enablin...

Wei Jiang, et al. ∙

research

∙ 04/29/2022

A Simple Method to Boost Human Pose Estimation Accuracy by Correcting the Joint Regressor for the Human3.6m Dataset

Many human pose estimation methods estimate Skinned Multi-Person Linear ...

Eric Hedlin, et al. ∙

The University of British Columbia

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