24 papers · ranked by Valyu relevance
Chandra N. Sekharan, George K. Thiruvathukal
Computer science (CS) education needs to evolve to support software and artificial intelligence (AI) systems engineering, and it needs to happen now -- precisely because the core intellectual contributions of CS have never been more important. We argue that traditional curricula, built around programming, data…
Chantal Enguehard, Guillaume Munch-Maccagnoni, Alberto Naibo
The concept of 'undone science' emerged in the 2010s in research in social sciences at the intersection of studies on social movements and of science and technology studies. It refers to research questions that are neglected, ignored, or left unfunded, even though they deserve to be explored. The aim of this special…
Baruch Garcia
We already know that several problems like the inequivalence of P and EXP as well as the undecidability of the acceptance problem and halting problem relativize. However, relativization is a limited tool which cannot separate other complexity classes. What has not been proven explicitly is whether the…
Minas Gadalla, Sotiris Nikoletseas, José Roberto de A. Amazonas
This research aimed to examine the interdisciplinary interaction between psychoanalysis and computer science, suggesting a mutually beneficial exchange. Indeed, psychoanalytic concepts can enrich technological applications that involve the human factor, such as social media and other interactive digital platforms. By…
Francesco Caravelli, Jean-Charles Delvenne
We develop a Koopman operator framework for studying the computational properties of dynamical systems. Specifically, we show that the resolvent of the Koopman operator provides a natural abstraction of halting, yielding a "Koopman halting problem that is recursively enumerable in general. For symbolic systems, such as…
K. L. Kirkpatrick
The theoretical foundation of neuroscience differs from that of artificial intelligence, and to bridge this gap with AI, we would need a new computing paradigm that describes both fields well. The gap came from mathematicians’ invention of computability theory, which was deliberately narrower than cognition and yet…
Christian Alexandra Rances, Rassel Aviel Sipe, Sherwin Baris, Adrian Lopez + 3 more
This study reported the development and evaluation of CoDeRS (subsequently referred to as the software), a web-based recommender system designed to assist students in identifying suitable computing degree programs (e.g., Computer Science, Data Science, Animation, Game Development, and Information Technology). The…
Abdullah Duaa, Jasem Hamoud
In this paper we explore fundamental concepts in computational complexity theory and the boundaries of algorithmic decidability. We examine the relationship between complexity classes P and NP, where L ∈ P implies the existence of a deterministic Turing machine solving L in polynomial time O(n k ). Central to our…
A. Sina Booeshaghi, Laura Luebbert, Lior Pachter
We develop a machine-automated approach for extracting results from papers, which we assess via a comprehensive review of the entire eLife corpus. Our method facilitates a direct comparison of machine and peer review, and sheds light on key challenges that must be overcome in order to facilitate AI-assisted science. In…
Jeremy Li, Alex Rubinsteyn, Sergey Feldman, Timothy O’Donnell + 18 more
Scientific computing has become a central component of modern scientific discovery. Yet many computational tools are developed by small, specialized teams under incentives that encourage the release of rapidly prototyped tooling without commensurate attention to engineering concerns, including performance and…
Authors not listed
Realizing the promise of artificial intelligence (AI) to accelerate scientific progress and deliver technological impact depends on how effectively AI can be integrated into real-world decision- making processes. As Peter Norvig states, “Somewhat remarkably, almost all AI research until very recently has assumed that…
Authors not listed
Synthetic accessibility is a key issue in the current compound generation. Unlike conventional approaches that assess synthetic accessibility after compound generation, the fragment-based method proposed in this study links the fragments in the reverse direction of the retrosynthesis analysis guaranteeing the synthetic…
Authors not listed
For decades, molecular visualization software has been fundamental to education and research in chemistry, structural biology, and materials science. These tools have enabled the inspection of structures, dynamics, and interactions, yet their reliance on two-dimensional (2D) interfaces imposes persistent limitations.…
Yukun Yang, Wolfgang Maass
Most current methods for goal-directed action selection in the face of changing goals and contingencies require DNNs or LLMs. Therefore they are less suited for implementation in edge devices, where low energy-consumption is imperative. The brain shows that similar functionality can be produced with just 20W, even with…
Authors not listed
Chemistry curricula often separate “wet” experimental work from “dry” computation, yet modern discovery increasingly demands both. This Perspective offers an instructor-ready roadmap to train “hybrid chemists” within existing courses. We distill recent advances in machine learning, automation, and real-time analytics…
Wade R. Boohar, Kayla Y. Xu, Nicole Black, Mahija Mogalipuvvu + 3 more
Computational methodology has become ubiquitous in biomedical research with the rise of big data analysis and popularity of artificial intelligence and machine learning. However, undergraduate bioinformatics education has largely struggled to keep pace with the demand for bioinformatics skills, due to a combination of…
Authors not listed
Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a…
Niels Kristian Madsen, Robert M. Ziolek, Daniel Kongsgaard, Christian Flohr Nielsen + 12 more
A great number of drug discovery programs fail due to poor in vivo efficacy and ADMET liabilities. On- and off-target ligand residence times can act as important drivers of these problems. However, the kinetics of ligand-protein residence times has historically been largely overlooked during early-stage drug discovery…
Authors not listed
Machine learning is increasingly used to predict reaction properties such as barrier heights, reaction energies, rates, or yields, as well as the underlying molecular geometries, including transition state structures. While such predictions have the potential to provide mechanistic insight for high-impact applications…
Aysha Naseer, Naif Almudawi, Hanan Aljuaid, Abdulwahab Alazeb + 4 more
In the published article, there was an error in Affiliation 2 for authors Naif Almudawi and Abdulwahab Alazeb. Instead of “2Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia,” it should be “2Department of Computer Science…
Syed Zubair Ahmad, Farhan Qamar, Hamdan Alshehri, Fathe Jeribi + 3 more
There is an error in affiliation 2 for authors Hamdan Alshehri, Fathe Jeribi, Ali Tahir, Shams Tabrez Siddiqui and Jayabrabu Ramakrishnan. The correct affiliation 2 is: Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan 45142, Saudi Arabia.
Jared Reiling, Nancy Padilla-Coreano, Dhruvi Patel, Flavio Frohlich + 1 more
Capturing naturalistic behavioral dynamics is essential for understanding social interaction in ecologically valid settings. Existing investigations of naturalistic social interaction rely on time-aggregated analysis methods better suited for task-based experiments, which lose the complex, moment-to-moment dynamics…
Carlos Calvo Tapia, José Antonio Villacorta-Atienza, Gonzalo Aparicio-Rodríguez, Paloma Manubens + 3 more
Time compaction theory is a general framework explaining how a brain can efficiently deal with dynamic situations occurring in, e.g., sports games. It involves a geometric representation of the time dimension, which enables effective learning and strategic action planning. The theory has recently received experimental…
Eleni Adamidi, Serafeim Chatzopoulos, Alexandros C. Dimopoulos, Anastasia Krithara + 5 more
Artificial intelligence is increasingly used in Life Sciences, though the pace and direction of adoption varies widely across countries. To map the Greek landscape, we combined two complementary approaches, a data-driven analysis of 916,824 AI-related life-science papers harvested from OpenAlex and PubMed and a…