17 papers · ranked by Valyu relevance
Benjamin R. Karin, Tony Gamble, Todd R. Jackman
Marker selection has emerged as an important component of phylogenomic study design due to rising concerns of the effects of gene tree estimation error, model misspecification, and data-type differences. Researchers must balance various trade-offs associated with locus length and evolutionary rate among other factors.…
Benjamin R Karin, Tony Gamble, Todd R Jackman, Nicolas Vidal
Marker selection has emerged as an important component of phylogenomic study design due to rising concerns of the effects of gene tree estimation error, model misspecification, and data-type differences. Researchers must balance various trade-offs associated with locus length and evolutionary rate among other factors.…
Zhaolin Gao, Jonathan Chang, Wenhao Zhan, Owen Oertell + 6 more
'Kianté Brantley' 'Thorsten Joachims' 'J. Andrew Bagnell' 'Jason D. Lee' 'Wen Sun'] While originally developed for continuous control problems, Proximal Policy Optimization (PPO) has emerged as the work-horse of a variety of reinforcement learning (RL) applications, including the fine-tuning of generative models.…
Pervez Shaik, Prosenjit Biswas, Abhinav Thorat, Ravi Kolla + 1 more
Sequential recommender systems typically infer user preferences through single-pass encoding of interaction histories without iterative refinement, relying on increasingly deep architectures to capture complex patterns. In this work, we revisit sequential recommendation from a recursive inference perspective: can user…
Zhenglong Zhou, Michael J. Kahana, Anna C. Schapiro
Replay in the brain is not a simple recapitulation of recent experience, with awake replay often unrolling in reverse temporal order upon receipt of reward, in a manner dependent on reward magnitude. These findings have led to the proposal that replay is optimized for learning value-based predictions in accordance with…
Alicia Marco, Pezhman Ashoo, Samanta Hernández-García, Pedro Martínez-Rodríguez + 6 more
A series of rhenium(I) complexes of the type fac-[Re(CO)3(N^N)L]0/+, Re1-Re9, was synthesized, where N^N = benzimidazole-derived bidentate ligand with an ester functionality and L = chloride or pyridine-type ligand. The new compounds demonstrated potent activity toward ovarian A2780 cancer cells. The most active…
Mariya Lysenkova Wiklander, Gustav Arvidsson, Ignas Bunikis, Anders Lundmark + 7 more
Long- and short-read sequencing are integrated to detail the genomic and transcriptomic characteristics of the cell line REH, a model for pediatric B-cell acute lymphoblastic leukemia.
Sabine Eschrig, Milena Schäffer, Lin-Jie Shu, Tina Illig + 3 more
The S-domain-type receptor-like kinase (SD-RLK) LIPOOLIGOSACCHARIDE-SPECIFIC REDUCED ELICITATION (LORE) from Arabidopsis thaliana is a pattern recognition receptor that senses medium-chain 3-hydroxy fatty acids, such as 3-hydroxydecanoic acid (3-OH-C10:0), to activate pattern-triggered immunity. Here, we show that LORE…
Jiayu Li, Hanyu Li, Zhiyu He, Weizhi Ma + 3 more
As research advances, various recommendation tasks, experimental settings, and optimization targets emerge. Recommendation tasks, starting from rating predictions [24] and top-k recommendations [42, 48], have extended to recent interests in CTR/CVR prediction [41, 60, 65] and re-ranking tasks [38, 39]. Meanwhile…
Fabian M. Renz, Shany Grossman, Nathaniel D. Daw, Peter Dayan + 2 more
Generalizing from previous experience in value-based tasks requires discovering and exploiting hidden structure to draw inferences beyond direct observations, and thereby update information about the values of states. We combined behavior, functional magnetic resonance imaging, and computational modeling to test how…
Yuanqing Yu, Chongming Gao, Jiawei Chen, Heng Tang + 4 more
'Qian Chen' 'Weizhi Ma' 'Min Zhang'] Reinforcement Learning (RL)-Based Recommender Systems (RSs) are increasingly recognized for their ability to improve long-term user engagement. Yet, the field grapples with challenges such as the absence of accessible frameworks, inconsistent evaluation standards, and the complexity…
Haoran Ling, Yuecheng Li, Zeyu Song, Jing Yao + 4 more
Optimizing modern recommender models still depends heavily on engineers manually iterating over architectural, objective, and training-strategy changes. While LLM-based agents can automate this trial-and-error process, allowing the LLM to both select modification directions and generate concrete hypotheses often leads…
Emma L. Roscow, Timothy Howe, Nathan F. Lepora, Matthew W. Jones
Neural activity encoding recent experiences is replayed during sleep and rest to promote consolidation of memories. However, precisely which features of experience influence replay prioritisation to optimise adaptive behaviour remains unclear. Here, we trained adult male rats on a novel maze-based reinforcement…
Eileen O. Dareng, Sally N. Adebamowo, Olabimpe R. Eseyin, Michael K. Odutola + 2 more
In this study of test-retest reliability of self-reported sexual behavior using interviewer administered questionnaires, we found that self-report of sexual behaviors was reasonably reliable overall. However, we observed varying levels of reliability based on the nature of sexual behavior reported. The reports on…
Ying Shi, Rong Ma, Tianjian Yang, Mohammad Masukujjaman
This paper studies the recycling and remanufacturing mode and sales channel issues in the closed-loop supply chain. Specifically, this study establishes an e-commerce closed-loop supply chain consisting of a manufacturer and an e-commerce platform, and divides the recycling model into recycling by the manufacturer or…
Authors not listed
Electrochemical impedance spectroscopy (EIS) is one of the most widely deployed methods to characterise electrochemical systems such as batteries, fuel cells or electrolyzers. The distribution of relaxation times (DRT) represents a technique to simplify EIS data by deconvolution with a suitable kernel, while with…
Tricia X. F. Seow, Jessica McFadyen, Raymond J. Dolan, Tobias U. Hauser
Humans often make irrational decisions when facing uncertain or aversive future events despite careful deliberation. How we make choices, including irrational ones^1,2^, has been the object of extensive study both behaviourally and neurally^3–6^ and is the focus of influential behavioural economic theories^7–9^. Yet…