Activation Compression of Graph Neural Networks Using Block-Wise Quantization with Improved Variance Minimization

S Eliassen, R Selvan - ICASSP 2024-2024 IEEE International …, 2024 - ieeexplore.ieee.org
Efficient training of large-scale graph neural networks (GNNs) has been studied with a
specific focus on reducing their memory consumption. Work by Liu et al.(2022) proposed …

Monitor the energy and carbon emissions of process-based models: ProcessC

Z Li, Z Qi, B Li, J Xu, R Wu, Y Liu, W Smith - Resources, Conservation and …, 2025 - Elsevier
Sustainable modelling to reduce carbon emissions from heavy computations is being
adopted in machine learning communities. However, this concept has not been considered …

Carbon Accounting in the Digital Industry: The Need to Move towards Decision Making in Uncertainty

G Samuel, F Lucivero, B Knowles, K Wright - Sustainability, 2024 - mdpi.com
In this paper, we present findings from a qualitative interview study, which highlights the
difficulties and challenges with quantifying carbon emissions and discusses how to move …

Is Adversarial Training with Compressed Datasets Effective?

T Chen, R Selvan - ar** Study
K Chadli, G Botterweck, T Saber - Proceedings of the 4th Workshop on …, 2024 - dl.acm.org
The integration of Machine Learning (ML) across public and industrial sectors has become
widespread, posing unique challenges in comparison to conventional software development …

Equity through Access: A Case for Small-scale Deep Learning

R Selvan, B Pepin, C Igel, G Samuel… - arxiv preprint arxiv …, 2024 - arxiv.org
The recent advances in deep learning (DL) have been accelerated by access to large-scale
data and compute. These large-scale resources have been used to train progressively …

Limits to AI Growth: The Ecological and Social Consequences of Scaling

E Bhardwaj, R Alexander, C Becker - arxiv preprint arxiv:2501.17980, 2025 - arxiv.org
The accelerating development and deployment of AI technologies depend on the continued
ability to scale their infrastructure. This has implied increasing amounts of monetary …

Harnessing ai for sustainable architecture: A tows analysis of environmental, economic, and social impacts in design

JD Salazar Rodriguez - Economic, and Social Impacts in Design …, 2024 - papers.ssrn.com
This study explores the role of Artificial Intelligence (AI) in enhancing sustainability within
architectural design, focusing on environmental, economic, and social dimensions. With AI …

[PDF][PDF] A Critical Analysis of Machine Learning Eco-feedback Tools through the Lens of Sustainable HCI

S Gorucu, L Morais, G Panagiotidou - CHI Conference on Human …, 2025 - kclpure.kcl.ac.uk
Authors' Contact Information: Sinem Görücü, sinem. gorucu@ kcl. ac. uk, King's College
London, London, UK; Luiz A. Morais, lamm@ cin. ufpe. br, Universidade Federal de …

[HTML][HTML] The Climate and Sustainability Implications of Generative AI

N Bashir, P Donti, J Cuff, S Sroka, M Ilic, V Sze… - 2024 - mit-genai.pubpub.org
The rapid expansion of generative artificial intelligence (Gen-AI) is propelled by its
perceived benefits, significant advancements in computing efficiency, corporate …