Kavli Affiliate: Oskar Painter | First 5 Authors: Mo Chen, John Clai Owens, Harald Putterman, Max Schäfer, Oskar Painter | Summary: Noise within solid-state systems at low temperatures, where many of the degrees of freedom of the host material are frozen out, can typically be traced back to material defects that support low-energy excitations. These […]
Kavli Affiliate: Michael Wimmer | First 5 Authors: Markus Schütz, Lukas Herzberger, Michael Wimmer, , | Summary: About: We propose an incremental LOD generation approach for point clouds that allows us to simultaneously load points from disk, update an octree-based level-of-detail representation, and render the intermediate results in real time while additional points are still […]
Kavli Affiliate: Xiang Zhang | First 5 Authors: Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang | Summary: Graph Contrastive Learning (GCL) has emerged as a popular unsupervised graph representation learning method. However, it has been shown that GCL is vulnerable to adversarial attacks on both the graph structure and node attributes. Although […]
Kavli Affiliate: Radhika Nagpal | First 5 Authors: Darren Chiu, Radhika Nagpal, Bahar Haghighat, , | Summary: Robot swarms can be tasked with a variety of automated sensing and inspection applications in aerial, aquatic, and surface environments. In this paper, we study a simplified two-outcome surface inspection task. We task a group of robots to […]
Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain […]
Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain […]
Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain […]
Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Prompt learning has recently become a very efficient transfer learning paradigm for Contrastive Language Image Pretraining (CLIP) models. Compared with fine-tuning the entire encoder, prompt learning can obtain highly competitive results by optimizing only a small number […]
Kavli Affiliate: Michael Wimmer | First 5 Authors: Lukas Lipp, David Hahn, Pierre Ecormier-Nocca, Florian Rist, Michael Wimmer | Summary: Controlling light is a central element when composing a scene, enabling artistic expression, as well as the design of comfortable living spaces. In contrast to previous camera-based inverse rendering approaches, we introduce a novel method […]
Kavli Affiliate: Michael Wimmer | First 5 Authors: Lukas Lipp, David Hahn, Pierre Ecormier-Nocca, Florian Rist, Michael Wimmer | Summary: Differentiable rendering methods promise the ability to optimize various parameters of 3d scenes to achieve a desired result. However, lighting design has so far received little attention in this field. In this paper, we introduce […]