Multi-scale Diffusion Denoised Smoothing

Along with recent diffusion models, randomized smoothing has become one of a few tangible approaches that offers adversarial robustness to models at scale, e.g., those of large pre-trained models. Specifically, one can perform randomized smoothing on any classifier via a simple "denoise-and-classify" pipeline, so-called denoised smoothing, given that an accurate denoiser is available - such as diffusion model. In this paper, we present scalable methods to address the current trade-off between certified robustness and accuracy in denoised smoothing. Our key idea is to "selectively" apply smoothing among multiple noise scales, coined multi-scale smoothing, which can be efficiently implemented with a single diffusion model. This approach also suggests a new objective to compare the collective robustness of multi-scale smoothed classifiers, and questions which representation of diffusion model would maximize the objective. To address this, we propose to further fine-tune diffusion model (a) to perform consistent denoising whenever the original image is recoverable, but (b) to generate rather diverse outputs otherwise. Our experiments show that the proposed multi-scale smoothing scheme combined with diffusion fine-tuning enables strong certified robustness available with high noise level while maintaining its accuracy close to non-smoothed classifiers.Comment: Published as a conference paper at NeurIPS 2023; Code is available at https://github.com/jh-jeong/smoothing-multiscal

Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder

Despite its practical importance across a wide range of modalities, recent advances in self-supervised learning (SSL) have been primarily focused on a few well-curated domains, e.g., vision and language, often relying on their domain-specific knowledge. For example, Masked Auto-Encoder (MAE) has become one of the popular architectures in these domains, but less has explored its potential in other modalities. In this paper, we develop MAE as a unified, modality-agnostic SSL framework. In turn, we argue meta-learning as a key to interpreting MAE as a modality-agnostic learner, and propose enhancements to MAE from the motivation to jointly improve its SSL across diverse modalities, coined MetaMAE as a result. Our key idea is to view the mask reconstruction of MAE as a meta-learning task: masked tokens are predicted by adapting the Transformer meta-learner through the amortization of unmasked tokens. Based on this novel interpretation, we propose to integrate two advanced meta-learning techniques. First, we adapt the amortized latent of the Transformer encoder using gradient-based meta-learning to enhance the reconstruction. Then, we maximize the alignment between amortized and adapted latents through task contrastive learning which guides the Transformer encoder to better encode the task-specific knowledge. Our experiment demonstrates the superiority of MetaMAE in the modality-agnostic SSL benchmark (called DABS), significantly outperforming prior baselines. Code is available at https://github.com/alinlab/MetaMAE.Comment: Accepted to NeurIPS 2023. The first two authors contributed equall

M2m: Imbalanced Classification via Major-to-minor Translation

In most real-world scenarios, labeled training datasets are highly class-imbalanced, where deep neural networks suffer from generalizing to a balanced testing criterion. In this paper, we explore a novel yet simple way to alleviate this issue by augmenting less-frequent classes via translating samples (e.g., images) from more-frequent classes. This simple approach enables a classifier to learn more generalizable features of minority classes, by transferring and leveraging the diversity of the majority information. Our experimental results on a variety of class-imbalanced datasets show that the proposed method improves the generalization on minority classes significantly compared to other existing re-sampling or re-weighting methods. The performance of our method even surpasses those of previous state-of-the-art methods for the imbalanced classification.Comment: 12 pages; CVPR 202

Collaborative Score Distillation for Consistent Visual Synthesis

Generative priors of large-scale text-to-image diffusion models enable a wide range of new generation and editing applications on diverse visual modalities. However, when adapting these priors to complex visual modalities, often represented as multiple images (e.g., video), achieving consistency across a set of images is challenging. In this paper, we address this challenge with a novel method, Collaborative Score Distillation (CSD). CSD is based on the Stein Variational Gradient Descent (SVGD). Specifically, we propose to consider multiple samples as "particles" in the SVGD update and combine their score functions to distill generative priors over a set of images synchronously. Thus, CSD facilitates seamless integration of information across 2D images, leading to a consistent visual synthesis across multiple samples. We show the effectiveness of CSD in a variety of tasks, encompassing the visual editing of panorama images, videos, and 3D scenes. Our results underline the competency of CSD as a versatile method for enhancing inter-sample consistency, thereby broadening the applicability of text-to-image diffusion models.Comment: Project page with visuals: https://subin-kim-cv.github.io/CSD

Lenzimycins A and B, metabolites with antibacterial properties from Brevibacillus sp. associated with the dung beetle Onthophagus lenzii

Symbiotic microorganisms associated with insects can produce a wide array of metabolic products, which provide an opportunity for the discovery of useful natural products. Selective isolation of bacterial strains associated with the dung beetle, Onthophagus lenzii, identified two strains, of which the antibiotic-producing Brevibacillus sp. PTH23 inhibited the growth of Bacillus sp. CCARM 9248, which is most closely related to the well-known entomopathogen, Bacillus thuringiensis. A comprehensive chemical investigation based on antibiotic activity discovered two new antibiotics, named lenzimycins A and B (1-2), which inhibited growth of Bacillus sp. CCARM 9248. The 1H and 13C NMR, MS, MS/MS, and IR analyses elucidated the structures of 1 and 2, which comprised a novel combination of fatty acid (12-methyltetradecanoic acid), glycerol, sulfate, and N-methyl ethanolamine. Furthermore, the acid hydrolysis of 1 revealed the absolute configuration of 12-methyltetradecanoic acid as 12S by comparing its optical rotation value with authentic (R)- and (S)-12-methyltetradecanoic acid. In addition to inhibition of Bacillus sp. CCARM 9248, lenzimycins A and B were found to inhibit the growth of some human pathogenic bacteria, including Enterococcus faecium and certain strains of Enterococcus faecalis. Furthermore, the present study elucidated that lenzimycins A and B activated a reporter system designed to detect the bacterial cell envelope stress, thereby indicating an activity against the integrity of the bacterial cell wall

Marine natural products: Chemistry and Chemosystematics of the Gorgonian Genus Eunicea and Exploratory Studies of the Secondary Metabolites of Marine Fungi

Secondary metabolites of the Caribbean gorgonian genus Eunicea were extensively investigated through the systematic collection and assortment based on thin layer chromatographic analysis. In addition. the chemical characters of Eunicea species were compared to the morphological classifications. In total, 792 individual colonies were collected from various locations. Based upon the TLC characters. 780 colonies were divided into 11 chemotypes which cover 8 of 12 taxonomically defined species and 4 new species.Detailed chemical investigation resulted in the isolation of 39 new metabolites. along with 9 previously described compounds. Diterpenoids were the major group of metabolites, and cembranes were the most commonly encountered class. Other diterpenoids were dolabellanes, cubitanes, asperketals, fuscol and fuscol glycosides. Metabolites of three unprecedented classes were also isolated: C28 reduced quinones, trisnorditerpenoids and a diterpene glycoside of the "extended eremophilane" class. The irregular diterpenoid cubitanes were determined to be formed by a photochemically induced 1,3-acyl migration of a cembrane precursor.Several chemotypes were collected from more than one location. Each chemotype contained only one or two classes of very distinct metabolites. In the case where metabolites of a sing!e class were isolated from more than one chemotype, there were great structural similarities among metabo!ites from the same chemotype, while metabolites from different chemotypes often showed very distinct patterns of functionalization.Chemical characteristics of each chemotype were compared to the morphological classification. The chemical contents were clearly different between the Eunicea subgenera, Eunicea sensu strictu and Euniceopsis. Eunicea s.s. was a chemically homogeneous group, all containing cembrane lactones. In contrast, Euniceopsis showed species-specific distribution of metabolites. Comparison of chemical contents revealed that for the chemosystematics of the Eunicea, types and distributions of functional groups were as important characters as the carbon skeletons of metabolites.One hundred twenty one marine fungal strains were either isolated from various habitats or obtained from mycologists. The fungi were cultivated in liquid media. Thirty eight extracts showed significant anti-microbial activities and/or cytotoxicity. Based upon the results of bioactivity tests, TLC analysis, and proton NMR spectroscopic analysis of the extracts, several strains were chemically investigatigated.From Asteromyces cruciatus, gliovictin, a metabolite of the gliotoxin class was isolated. Also, several trichothecenes of the verrucarin and roridin classes were isolated from an unknown fungus. In addition, a few small-sized metabolites were isolated. The future of marine fungi for chemical investigation is discussed

Marine natural products: Chemistry and Chemosystematics of the Gorgonian Genus Eunicea and Exploratory Studies of the Secondary Metabolites of Marine Fungi

Secondary metabolites of the Caribbean gorgonian genus Eunicea were extensively investigated through the systematic collection and assortment based on thin layer chromatographic analysis. In addition. the chemical characters of Eunicea species were compared to the morphological classifications. In total, 792 individual colonies were collected from various locations. Based upon the TLC characters. 780 colonies were divided into 11 chemotypes which cover 8 of 12 taxonomically defined species and 4 new species.Detailed chemical investigation resulted in the isolation of 39 new metabolites. along with 9 previously described compounds. Diterpenoids were the major group of metabolites, and cembranes were the most commonly encountered class. Other diterpenoids were dolabellanes, cubitanes, asperketals, fuscol and fuscol glycosides. Metabolites of three unprecedented classes were also isolated: C28 reduced quinones, trisnorditerpenoids and a diterpene glycoside of the "extended eremophilane" class. The irregular diterpenoid cubitanes were determined to be formed by a photochemically induced 1,3-acyl migration of a cembrane precursor.Several chemotypes were collected from more than one location. Each chemotype contained only one or two classes of very distinct metabolites. In the case where metabolites of a sing!e class were isolated from more than one chemotype, there were great structural similarities among metabo!ites from the same chemotype, while metabolites from different chemotypes often showed very distinct patterns of functionalization.Chemical characteristics of each chemotype were compared to the morphological classification. The chemical contents were clearly different between the Eunicea subgenera, Eunicea sensu strictu and Euniceopsis. Eunicea s.s. was a chemically homogeneous group, all containing cembrane lactones. In contrast, Euniceopsis showed species-specific distribution of metabolites. Comparison of chemical contents revealed that for the chemosystematics of the Eunicea, types and distributions of functional groups were as important characters as the carbon skeletons of metabolites.One hundred twenty one marine fungal strains were either isolated from various habitats or obtained from mycologists. The fungi were cultivated in liquid media. Thirty eight extracts showed significant anti-microbial activities and/or cytotoxicity. Based upon the results of bioactivity tests, TLC analysis, and proton NMR spectroscopic analysis of the extracts, several strains were chemically investigatigated.From Asteromyces cruciatus, gliovictin, a metabolite of the gliotoxin class was isolated. Also, several trichothecenes of the verrucarin and roridin classes were isolated from an unknown fungus. In addition, a few small-sized metabolites were isolated. The future of marine fungi for chemical investigation is discussed