Adaptive comfort and climate-sensitive architecture: how occupants feel in their homes?

Postprint (published version

Relating Regularization and Generalization through the Intrinsic Dimension of Activations

Given a pair of models with similar training set performance, it is natural to assume that the model that possesses simpler internal representations would exhibit better generalization. In this work, we provide empirical evidence for this intuition through an analysis of the intrinsic dimension (ID) of model activations, which can be thought of as the minimal number of factors of variation in the model's representation of the data. First, we show that common regularization techniques uniformly decrease the last-layer ID (LLID) of validation set activations for image classification models and show how this strongly affects generalization performance. We also investigate how excessive regularization decreases a model's ability to extract features from data in earlier layers, leading to a negative effect on validation accuracy even while LLID continues to decrease and training accuracy remains near-perfect. Finally, we examine the LLID over the course of training of models that exhibit grokking. We observe that well after training accuracy saturates, when models ``grok'' and validation accuracy suddenly improves from random to perfect, there is a co-occurent sudden drop in LLID, thus providing more insight into the dynamics of sudden generalization.Comment: NeurIPS 2022 OPT and HITY workshop

Experimental Transmission of Kaposi's Sarcoma–Associated Herpesvirus (Kshv/Hhv-8) to Scid-Hu Thy/Liv Mice

Kaposi's sarcoma–associated herpesvirus (KSHV/HHV-8) is a novel human lymphotropic herpesvirus linked to several human neoplasms. To date, no animal model for infection by this virus has been described. We have examined the susceptibility of C.B-17 scid/scid mice implanted with human fetal thymus and liver grafts (SCID-hu Thy/Liv mice) to KSHV infection. KSHV virions were inoculated directly into the implants, and viral DNA and mRNA production was assayed using real-time quantitative polymerase chain reaction. This revealed a biphasic infection, with an early phase of lytic replication accompanied and followed by sustained latency. Ultraviolet irradiation of the inoculum abolished all DNA- and mRNA-derived signals, and infection was inhibited by ganciclovir. Viral gene expression was most abundant in CD19+ B lymphocytes, suggesting that this model faithfully mimics the natural tropism of this virus. Short-term coinfection with HIV-1 did not alter the course of KSHV replication, nor did KSHV alter levels of HIV-1 p24 during the acute phase of the infection. Although no disease was evident in infected animals, SCID-hu Thy/Liv mice should allow the detailed study of KSHV tropism, latency, and drug susceptibility

EC(5)S Ubiquitin Complex Is Recruited by KSHV Latent Antigen LANA for Degradation of the VHL and p53 Tumor Suppressors

Cellular protein degradation pathways can be utilized by viruses to establish an environment that favors their propagation. Here we report that the Kaposi's sarcoma–associated herpesvirus (KSHV)-encoded latency-associated nuclear antigen (LANA) directly functions as a component of the EC(5)S ubiquitin complex targeting the tumor suppressors von Hippel-Lindau (VHL) and p53 for degradation. We have characterized a suppressor of cytokine signaling box-like motif within LANA composed of an Elongin B and C box and a Cullin box, which is spatially located at its amino and carboxyl termini. This motif is necessary for LANA interaction with the Cul5–Elongin BC complex, to promote polyubiquitylation of cellular substrates VHL and p53 in vitro via its amino- and carboxyl-terminal binding domain, respectively. In transfected cells as well as KSHV-infected B lymphoma cells, LANA expression stimulates degradation of VHL and p53. Additionally, specific RNA interference–mediated LANA knockdown stabilized VHL and p53 in primary effusion lymphoma cells. Thus, manipulation of tumor suppressors by LANA potentially provides a favorable environment for progression of KSHV-infected tumor cells

CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds

Precision measurements and new physics searches at the Large Hadron Collider require efficient simulations of particle propagation and interactions within the detectors. The most computationally expensive simulations involve calorimeter showers. Advances in deep generative modelling - particularly in the realm of high-dimensional data - have opened the possibility of generating realistic calorimeter showers orders of magnitude more quickly than physics-based simulation. However, the high-dimensional representation of showers belies the relative simplicity and structure of the underlying physical laws. This phenomenon is yet another example of the manifold hypothesis from machine learning, which states that high-dimensional data is supported on low-dimensional manifolds. We thus propose modelling calorimeter showers first by learning their manifold structure, and then estimating the density of data across this manifold. Learning manifold structure reduces the dimensionality of the data, which enables fast training and generation when compared with competing methods.Comment: Accepted to the Machine Learning and the Physical Sciences Workshop at NeurIPS 202

Effective Control of Chronic γ-Herpesvirus Infection by Unconventional MHC Class Ia–Independent CD8 T Cells

Control of virus infection is mediated in part by major histocompatibility complex (MHC) Class Ia presentation of viral peptides to conventional CD8 T cells. Although important, the absolute requirement for MHC Class Ia–dependent CD8 T cells for control of chronic virus infection has not been formally demonstrated. We show here that mice lacking MHC Class Ia molecules (K(b−/−)xD(b−/−) mice) effectively control chronic γ-herpesvirus 68 (γHV68) infection via a robust expansion of β(2)-microglobulin (β(2)-m)-dependent, but CD1d-independent, unconventional CD8 T cells. These unconventional CD8 T cells expressed: (1) CD8αβ and CD3, (2) cell surface molecules associated with conventional effector/memory CD8 T cells, (3) TCRαβ with a significant Vβ4, Vβ3, and Vβ10 bias, and (4) the key effector cytokine interferon-γ (IFNγ). Unconventional CD8 T cells utilized a diverse TCR repertoire, and CDR3 analysis suggests that some of that repertoire may be utilized even in the presence of conventional CD8 T cells. This is the first demonstration to our knowledge that β(2)-m–dependent, but Class Ia–independent, unconventional CD8 T cells can efficiently control chronic virus infection, implicating a role for β(2)-n–dependent non-classical MHC molecules in control of chronic viral infection. We speculate that similar unconventional CD8 T cells may be able to control of other chronic viral infections, especially when viruses evade immunity by inhibiting generation of Class Ia–restricted T cells