Genre
Contrastive dimension reduction: when and how?
Dimension reduction (DR) is an important and widely studied technique in exploratory data analysis.
SequentialAttention+ + for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
Pruning methods for neural networks [LeCun et al., 1989] replace dense weight matrices by sparse
IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL *Pascal Leroy
In IMP, a multi-component engineering system is subject to a risk of failure due to its components' damage condition.
Geometric Neural Diffusion Processes Emile Mathieu University Of Cambridge Vincent Dutordoir
Traditional denoising diffusion models are defined on finite-dimension Euclidean spaces (Song and Ermon, 2019; Song et al., 2021; Ho et al., 2020; Dhariwal and Nichol, 2021).
Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models
We conduct extensive experiments on various benchmark datasets, empirically demonstrate the effectiveness of Terra.
Conformal Alignment: Knowing When to Trust Foundation Models with Guarantees Y u Gui
Before deploying outputs from foundation models in high-stakes tasks, it is imperative to ensure that they align with human values.
Weakly Supervised 3D Open-vocabulary Segmentation
Given the super-rich semantics in 3D scenes, a crucial aspect of this task is achieving open-vocabulary segmentation that can handle regions and objects of various semantics including those with long-tail distributions.
A Benchmark Task Details
In the United States, health insurance is a critical component of individuals' ability to access health care.