Better together : project book by Ho, Phoebe Zoe, Heng, Diana Basil Li Jiao, Goh, Dylon Tong Yang, Teo, Lauren Marissa

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The next train = 下一班车 by Lou, Mei Jun

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Housing development box by Lim, Wan Ying

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The clay vessel by Ang, Jo Wen Wen

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Bodhi : project journey from a producer’s perspective by Liu, ZhangTeng

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Bodhi by Liu, ZhangTeng, Png, Zhen Yu

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Lattice codes for the Gaussian wiretap channel by Belfiore, Jean-Claude, Oggier, Frederique, Sole, Patrick

“…It has been shown recently that coding for the Gaussian Wiretap Channel can be done with nested lattices. A fine lattice intended to the legitimate user must be designed as a usual lattice code for the Gaussian Channel, while a coarse lattice is added to introduce confusion at the eavesdroppper, whose theta series must be minimized. …”
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Markerless aerial-terrestrial co-registration of forest point clouds using a deformable pose graph by Casseau, B, Chebrolu, N, Mattamala Aravena, M, Freissmuth, L, Fallon, M

“…Our method then uses these constraints in a pose graph formulation, which enables us to finely align the respective clouds while respecting spatial constraints introduced by the terrestrial SLAM scanning process. …”

Universal in-context approximation by prompting fully recurrent models by Petrov, A, Lamb, TA, Paren, A, Torr, PHS, Bibi, A

“…Zero-shot and in-context learning enable solving tasks without model fine-tuning, making them essential for developing generative model solutions. …”

Language models as hierarchy encoders by He, Y, Yuan, Z, Chen, J, Horrocks, I

“…We evaluate HITs against pre-trained LMs, standard fine-tuned LMs, and several hyperbolic embedding baselines, focusing on their capabilities in simulating transitive inference, predicting subsumptions, and transferring knowledge across hierarchies. …”

AI-assisted discovery of quantitative and formal models in social science by Balla, J, Huang, S, Dugan, O, Dangovski, R, Soljačić, M

“…We propose that this AI-assisted framework can bridge parametric and non-parametric models commonly employed in social science research by systematically exploring the space of non-linear models and enabling fine-grained control over expressivity and interpretability.…”

UWB antipodal Vivaldi antenna for monostatic configuration of through wall imaging applications by AHMED, SAJJAD, JORET, ARIFFUDDIN, KATIRAN, NORSHIDAH, PONNIRAN, ASMARASHID, ABDULLAH, M. F. L., ZAKARIA, ZAHRILADHA, SULONG, MUHAMMAD SUHAIMI

“…A specific stable gain of around 11.7 dB is achieved with good directivity and fine radiation patterns. Using this monostatic UWB antenna design, a TWI simulation-based experiment was carried out. …”
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Structure and phase engineering of 2D transition metal chalcogenides by Tang, Bijun

“…Moreover, the morphology of heterostructures can be engineered by fine-tuning the synthesis conditions. WS2 quantum well is also identified in the synthesized heterostructures, providing opportunities for studying novel optical properties and quantum confinement effects. …”
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Physics-informed machine learning for green data center operations by Wang, Ruihang

“…The evaluation shows that our approach saves 5.7% to 13.8% power usage compared with conventional feedback control and adapts 8x to 10x faster than native fine-tuning with at most 0.74C temperature overshoot. …”
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The Economics of Tropical Deforestation by Balboni, Clare, Berman, Aaron, Burgess, Robin, Olken, Benjamin A.

“…We begin by reviewing the methodological advances that have enabled measurement of forest loss at a fine spatial resolution across the globe. We then develop a simple benchmark model of deforestation based on classic models of natural resource extraction. …”
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An Energy and Area Estimation Plugin for Accelerator Architecture Simulation by Wu, Wendy

“…Accelergy is a tool that provides a good general framework for fine-grained energy and area estimation. However, output from simulation tools may not be compatible with Accelergy’s expected input format, which is the case for the custom simulator Accelsim. …”
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MLTCP: A Distributed Technique to Approximate Centralized Flow Scheduling For Machine Learning by Rajasekaran, Sudarsanan, Narang, Sanjoli, Zabreyko, Anton A., Ghobadi, Manya

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Unearthing roots by Lim, Ling Ern

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Looking Glass by Nur Mariyah Muhamad Afandi

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悟 · Know my heart by Wang, Ruimeng

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