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climate science

378 papers

#natural language process... Open access Aug 2026

Is Science Losing Its Objectivity in a Post-COVID World?

The COVID-19 pandemic served as a profound stress test for the global scientific enterprise, conducted under unprecedented public scrutiny and political pressure. This paper argues that the pandemic did not simply erode scientific objectivity but rather accelerated a necessary reckoning with its complex nature. Moving...

Kwan Hong TAN · 0 citations
#machine learning Open access Aug 2026

Can Democracy Survive in a Hyperconnected World?

This paper explores the complex and often contradictory relationship between hyperconnectivity and democracy. Drawing on novel theoretical frameworks inspired by quantum mechanics, network science, and temporal dynamics, we argue that the hyperconnected world is not simply an extension of the classical political landsc...

Kwan Hong TAN · 0 citations
#machine learning Open access Aug 2026

Can Democracy Survive in a Hyperconnected World?

This paper explores the complex and often contradictory relationship between hyperconnectivity and democracy. Drawing on novel theoretical frameworks inspired by quantum mechanics, network science, and temporal dynamics, we argue that the hyperconnected world is not simply an extension of the classical political landsc...

Kwan Hong TAN · 0 citations
#natural language process... Open access Aug 2026

Are Moral Facts Real or Constructed? Novel Theoretical Frameworks for Understanding Moral Ontology

The question of whether moral facts are real or constructed has dominated metaethical discourse for centuries, with traditional positions including moral realism, anti-realism, and constructivism offering competing accounts of moral ontology. This paper introduces four novel theoretical frameworks that transcend tradit...

Kwan Hong TAN · 0 citations
#natural language process... Open access Aug 2026

Are Moral Facts Real or Constructed? Novel Theoretical Frameworks for Understanding Moral Ontology

The question of whether moral facts are real or constructed has dominated metaethical discourse for centuries, with traditional positions including moral realism, anti-realism, and constructivism offering competing accounts of moral ontology. This paper introduces four novel theoretical frameworks that transcend tradit...

Kwan Hong TAN · 0 citations
#artificial intelligence Open access Jul 2026

Radical Empathy as a Moral Imperative in the 21st Century: The Empathic Imperative Thesis

This thesis examines whether radical empathy constitutes a moral imperative in the 21st century, presenting a novel theoretical framework termed the Empathic Imperative Thesis (EIT). Through comprehensive analysis of philosophical foundations, empirical evidence, and contemporary global challenges, this work argues tha...

Kwan Hong TAN · 0 citations
#artificial intelligence Book Open access Jul 2026

Radical Empathy as a Moral Imperative in the 21st Century: The Empathic Imperative Thesis

This thesis examines whether radical empathy constitutes a moral imperative in the 21st century, presenting a novel theoretical framework termed the Empathic Imperative Thesis (EIT). Through comprehensive analysis of philosophical foundations, empirical evidence, and contemporary global challenges, this work argues tha...

Kwan Hong TAN · 0 citations
#artificial intelligence Open access Jul 2026

Beyond Participatory Explanation: Ontological Reflexivity Theory as a Resolution to the Consciousness Emergence Problem

David Cota’s evaluation of the author’s “participatory explanation” approach to consciousness reveals fundamental conceptual problems that plague contemporary consciousness studies. Cota identifies a critical conflation between reason as a symbolic-operational function, and consciousness as a phenomenal-experiential fi...

Kwan Hong TAN · 0 citations
#artificial intelligence Open access Jul 2026

Beyond Participatory Explanation: Ontological Reflexivity Theory as a Resolution to the Consciousness Emergence Problem

David Cota’s evaluation of the author’s “participatory explanation” approach to consciousness reveals fundamental conceptual problems that plague contemporary consciousness studies. Cota identifies a critical conflation between reason as a symbolic-operational function, and consciousness as a phenomenal-experiential fi...

Kwan Hong TAN · 0 citations
#machine learning Preprint Feb 2026

Symmetric Composition of Anisotropic Operators for Global Subseasonal-to-Seasonal Climate Forecasting

Accurate global Subseasonal-to-Seasonal (S2S) climate forecasting is critical for disaster preparedness and resource management, yet it remains challenging due to chaotic atmospheric dynamics. Despite advances in geometry-aware representations, existing methods do not specify how the zonal and meridional interactions t...

Zi-Yu Zhou, Yu-Chen Fang, Wei-Lin Ruan et al. · 0 citations
#machine learning Preprint Sep 2026

MW-Nowcast: Six-hour ensemble nowcasting of extreme precipitation

Microsoft Weather Nowcast is presented, a six-hour ensemble radar nowcasting model that jointly learns a deterministic predictor to capture organised precipitation structure shared across ensemble members, and a generator to produce diverse local residuals around this shared prediction.

Ning Wang, Zu-Liang Fang, Wei-Xin Jin et al. · 0 citations
#machine learning Preprint Sep 2026

Suitable Measures for the Potential Operational Utility of AI NWP Rainfall Forecasts Over Africa

A calibrated comparison of GraphCast, GenCast and the Functional Generative Network against the physical NWP model IFS for rainfall prediction across Africa highlights the potential of calibrated AI weather prediction to provide accessible and computationally efficient rainfall forecasts, while demonstrating the contin...

S. Nath, Docko Sow, Koomi Toussaint Amoussouvi et al. · 0 citations

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Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

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