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Patterns
Scopus
ISSN 2666-3899 · Elsevier · 269 artikel di indeks
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Artikel Jurnal
Navigating the manifold: A transformative approach to AI image generation
Using an external starting image and sparse action prompts, Transformative AI treats image generation as iterative navigation through an irregular, high-dimensional manifold. This user-guided process preserves expressive development and explores regions apparently inaccessible to text-to-image…
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Artikel Jurnal
Intentional policy graphs: A pipeline for explaining agent behavior through intentions
Summary: Agents increasingly operate in complex environments, where coherent behavior often emerges from opaque decision-making processes. While such systems can be highly effective, this lack of transparency limits trust, auditing, and meaningful human understanding. We introduce intentional…
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Artikel Jurnal
Breaking the glass ceiling: An interview with Yuhao (Jet) Zhou, María Óskarsdóttir, and Cristián Bravo
Despite years of attention to gender equality, women remain underrepresented on corporate boards. Zhou et al. explore how professional connections influence access to these positions and the reasons behind the underrepresentation.1 In this interview, three authors reflect on the inspiration behind…
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Artikel Jurnal
Organizing across disciplines to tackle shared computational challenges
The Science through Computation Initiative unites sixteen early-career computational scientists spanning physics, biology, chemistry, and neuroscience. Over nine months of workshops and hackathons, they agreed on “computational motifs,” fundamental challenges that recur across their scientific…
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Artikel Jurnal
Unveiling gender disparities in corporate board career paths using deep learning
Summary: In this study, we investigate the relationship between professional networks and gender disparities in corporate board appointments, focusing on publicly traded Canadian companies. Using data from over 19,000 senior managers and board members in more than 700 firms from 2000 to 2022, we…
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Artikel Jurnal
DestinyNet: A deep-learning framework for cell-fate analysis from lineage-tracing single-cell RNA sequencing data
Summary: Unraveling cell-development dynamics, including lineage commitment, differentiation, and disease progression, is fundamental to biology. Despite advances in single-cell omics and barcoding technologies, comprehensive frameworks for accurate, robust, and scalable cell-fate analysis using…
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Artikel Jurnal
BDI-Kit: An AI-powered toolkit for biomedical data harmonization
Summary: The wide availability of biomedical data, coupled with advanced analytics, holds unprecedented promise for scientific discovery and improved patient care; yet, heterogeneity across datasets remains a major barrier. Given the inherent diversity of biomedical domains, one-size-fits-all…
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Artikel Jurnal
Experimental and machine learning-based exploration of repurposed drugs reveals chemical features underlying phospholipidosis
Summary: Phospholipidosis (PLD) is a cellular adverse effect caused by, among other things, cationic amphiphilic drugs. There is interest within pharma discovery to predict this phenomenon, as it can impact the outcome of phenotypic cellular screens and significantly delay drug development…
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Artikel Jurnal
UbiQTree: Uncertainty quantification in XAI with tree ensembles
Summary: Explainable artificial intelligence (XAI) techniques, particularly Shapley additive explanations (SHAP), are essential for interpreting ensemble tree-based models in critical areas such as healthcare. However, SHAP values are often treated as point estimates that neglect uncertainty…
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Artikel Jurnal
TweetyBERT: Automated parsing of birdsong through self-supervised machine learning
Summary: Deep neural networks can be trained to parse animal vocalizations—serving to identify the units of communication and annotating sequences of vocalizations for subsequent statistical analysis. However, current methods rely on human-labeled data for training. The challenge of parsing animal…
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Artikel Jurnal
Closing the multichannel gap through computational reconstruction of interaction in super-resolution microscopy
Summary: Cellular function is defined by pathways that, in turn, are determined by distance-mediated interactions between and within subcellular organelles, protein complexes, and macromolecular structures. Multichannel super-resolution microscopy (SRM) is uniquely placed to quantify…
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Artikel Jurnal
Bringing AI participation down to scale
Summary: In 2023, OpenAI’s Democratic Inputs program funded 10 teams to design procedures for public participation in generative AI. In this perspective, we review the results of the project, drawing on interviews with some of the teams and our own experiences conducting participation exercises. We…
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Artikel Jurnal
SECONDGRAM: Self-conditioned diffusion with gradient manipulation for longitudinal MRI imputation
Summary: While individual MRI snapshots provide valuable insights, the longitudinal progression in repeated MRIs often holds more significant diagnostic and prognostic value. However, a scarcity of longitudinal datasets, comprising paired initial and follow-up scans, hinders the application of…
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Designing a large language model for chemists
In a recent issue of Cell Reports Physical Science, Zhao et al. introduced ChemDFM, a foundational large language model designed specifically for chemistry. The model bridges the gap between general-purpose language models and specialized chemical knowledge, including the integration of multimodal…
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Artikel Jurnal
Aligning large language models and geometric deep models for protein representation
Summary: In this study, we explore the alignment of multimodal representations between large language models (LLMs) and geometric deep models (GDMs) in the protein domain. We comprehensively evaluate three LLMs with four protein-specialized GDMs. Our work examines alignment factors from both model…
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Artikel Jurnal
FoodSky: A food-oriented large language model that can pass the chef and dietetic examinations
Summary: Food is the cornerstone of both survival and social life. With the increasing complexity of global dietary cultures, there is a growing demand for food intelligence to enable tasks like recipe recommendations and diet-disease correlation discovery. To address this, we introduce the…
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Artikel Jurnal
Starting a synthetic biological intelligence lab from scratch
Summary: Recent advances in artificial intelligence (AI) have led to the development and deployment of gigantic models trained on billions of samples. While training these models consumes enormous energy, the human brain produces similar outputs with dramatically lower data and energy requirements…
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Artikel Jurnal
Harnessing explainable AI to adaptively design catalysts for lithium-sulfur batteries
The exploration of efficient catalysts for sluggish sulfur redox reactions is pivotal for advancing lithium-sulfur batteries but remains inefficient through trial-and-error approaches. In a recent Joule study, Zhou, Li, and colleagues proposed an explainable-AI-based approach to intelligently…
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Artikel Jurnal
Evaluation of unsupervised learning algorithms for the classification of behavior from pose estimation data
Summary: Analyzing animal behavior is crucial for decoding brain function, modeling neurological disorders, and assessing therapeutics. Recent advances in pose-estimation tools like DeepLabCut and SLEAP have revolutionized behavioral analysis by enabling precise tracking of animal body movements…