ServiceNow AI Research

9

Learning Global Variations in Outdoor PM_2.5 Concentrations with Satellite Images
Here we present a new method of estimating global variations in outdoor PM2.5 concentrations using satellite images combined with …
Workshop at the International Conference on Machine Learning (ICML),  2019.
Paper Cite
Stochastic Neural Network with Kronecker Flow
Stochastic Neural Network with Kronecker Flow
Recent advances in variational inference enable the modelling of highly structured joint distributions, but are limited in their …
Workshop at the International Conference on Machine Learning (ICML),  2019.
Paper Cite
Adaptive Cross-Modal Few-shot Learning
Adaptive Cross-Modal Few-shot Learning
Metric-based meta-learning techniques have successfully been applied to few-shot classification problems. In this paper, we propose to …
Workshop at the International Conference on Learning Representations (ICLR),  2019.
Paper Cite Code
Adaptive Masked Weight Imprinting for Few-Shot Segmentation
Adaptive Masked Weight Imprinting for Few-Shot Segmentation
Deep learning has mainly thrived by training on large-scale datasets. However, for continual learning in applications such as robotics, …
Workshop at the International Conference on Learning Representations (ICLR),  2019.
Paper Cite Code
Adversarial Learning of General Transformations for Data Augmentation
Adversarial Learning of General Transformations for Data Augmentation
Data augmentation (DA) is fundamental against overfitting in large convolutional neural networks, especially with a limited training …
Workshop at the International Conference on Learning Representations (ICLR),  2019.
Paper Cite Code
Adversarial Mixup Resynthesizers
Adversarial Mixup Resynthesizers
In this paper, we explore new approaches to combining information encoded within the learned representations of auto-encoders. We …
Workshop at the International Conference on Learning Representations (ICLR),  2019.
Paper Cite Code
Planning with Latent SImulated Trajectories
Planning with Latent SImulated Trajectories
In this work, we draw connections between planning and latent variable models1. Specifically, planning can be seen as introducing …
Workshop at the International Conference on Learning Representations (ICLR),  2019.
Paper Cite
Reproducibility and Stability Analysis in Metric-Based Few-Shot Learning
We propose a study of the stability of several few-shot learning algorithms subject to variations in the hyper-parameters and …
Workshop at the International Conference on Learning Representations (ICLR),  2019.
Paper Cite
Towards Standardization of Data Licenses: The Montreal Data License
This paper provides a taxonomy for the licensing of data in the fields of artificial intelligence and machine learning. The …
Workshop at the International Conference on Learning Representations (ICLR),  2019.
Paper Cite
Adversarial Framing for Image and Video Classification
Adversarial Framing for Image and Video Classification
Neural networks are prone to adversarial attacks. In general, such attacks deteriorate the quality of the input by either slightly …
Student Abstract at the Association for the Advancement of Artificial Intelligence (AAAI),  2019.
Paper Cite Code