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Found 6 papers, 1 papers with code
Exploiting Inductive Biases in Video Modeling through Neural CDEs
We introduce a novel approach to video modeling that leverages controlled differential equations (CDEs) to address key challenges in video tasks, notably video interpolation and mask propagation.
Variable Length Embeddings
In this work, we introduce a novel deep learning architecture, Variable Length Embeddings (VLEs), an autoregressive model that can produce a latent representation composed of an arbitrary number of tokens.
Structure and Content-Guided Video Synthesis with Diffusion Models
Text-guided generative diffusion models unlock powerful image creation and editing tools.
Designing a Recurrent Neural Network to Learn a Motion Planner for High-Dimensional Inputs
The use of machine learning in the self-driving industry has boosted a number of recent advancements.
Modeling Image Quantization Tradeoffs for Optimal Compression
All Lossy compression algorithms employ similar compression schemes -- frequency domain transform followed by quantization and lossless encoding schemes.
Formal Analysis and Redesign of a Neural Network-Based Aircraft Taxiing System with VerifAI
We demonstrate a unified approach to rigorous design of safety-critical autonomous systems using the VerifAI toolkit for formal analysis of AI-based systems.
