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Found 5 papers, 2 papers with code
Variational Bayesian Last Layers
We introduce a deterministic variational formulation for training Bayesian last layer neural networks.
FlexModel: A Framework for Interpretability of Distributed Large Language Models
With the growth of large language models, now incorporating billions of parameters, the hardware prerequisites for their training and deployment have seen a corresponding increase.
A Comparison of Classical and Deep Reinforcement Learning Methods for HVAC Control
Reinforcement learning (RL) is a promising approach for optimizing HVAC control.
InterTrack: Interaction Transformer for 3D Multi-Object Tracking
We then perform a learned regression on each track/detection feature pair to estimate affinities, and use a robust two-stage data association and track management approach to produce the final tracks.
Bayesian Embeddings for Few-Shot Open World Recognition
As autonomous decision-making agents move from narrow operating environments to unstructured worlds, learning systems must move from a closed-world formulation to an open-world and few-shot setting in which agents continuously learn new classes from small amounts of information.
