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05/24/2023
Realistically distributing object placements in synthetic training data improves the performance of vision-based object detection models
When training object detection models on synthetic data, it is important...
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05/19/2023
Video Killed the HD-Map: Predicting Driving Behavior Directly From Drone Images
The development of algorithms that learn behavioral driving models using...
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06/17/2022
Conditional Permutation Invariant Flows
We present a novel, conditional generative probabilistic model of set-va...
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05/30/2022
Critic Sequential Monte Carlo
We introduce CriticSMC, a new algorithm for planning as inference built ...
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05/12/2021
MATE-KD: Masked Adversarial TExt, a Companion to Knowledge Distillation
The advent of large pre-trained language models has given rise to rapid ...
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04/22/2021
Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulation
We develop a deep generative model built on a fully differentiable simul...
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12/31/2020
Towards Zero-Shot Knowledge Distillation for Natural Language Processing
Knowledge Distillation (KD) is a common knowledge transfer algorithm use...
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06/21/2020
Mapping Low-Resolution Images To Multiple High-Resolution Images Using Non-Adversarial Mapping
Several methods have recently been proposed for the Single Image Super-R...
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02/08/2020
Time-aware Large Kernel Convolutions
To date, most state-of-the-art sequence modelling architectures use atte...
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10/02/2019
Distilled embedding: non-linear embedding factorization using knowledge distillation
Word-embeddings are a vital component of Natural Language Processing (NL...
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05/23/2019
