21 papers · ranked by Valyu relevance
Gidon Levakov, Joshua Faskowitz, Galia Avidan, Olaf Sporns
Connectome embedding (CE) are compact vectorized representations of brain nodes capturing their context in the global network topology. Applied to group-averaged structural connectivity, CE was previously shown to capture relations between inter-hemispheric homologous brain regions and uncover putative missing edges…
Chirag Jain, Sravanthi Upadrasta Naga Sita, Avinash Sharma, Bapi Raju Surampudi
The intricate link between brain functional connectivity (FC) and structural connectivity (SC) is explored through models performing diffusion on SC to derive FC, using varied methodologies from single to multiple graph diffusion kernels. However, existing studies have not correlated diffusion scales with specific…
Chong Jiang, Wu Zhao, Miao Yu, Kai Zhang + 1 more
With the continued development of natural gas extraction technologies, the accurate determination of downhole temperature and pressure has become increasingly important. It is crucial for the optimization of gas well production and an important measure to prevent accidents. However, existing logging instruments have a…
Qiujian Xu, Meihui Li, Guoqiang Chen, Xiubo Ren + 10 more
'Junrui Li' 'Xinran Yuan' 'Siqi Liu' 'Miaomiao Yang' 'Mufan Chen' 'Bo Wang' 'Peng Zhang' 'Huiguo Ma' 'Jin Huang'] This study designs and develops a wearable exoskeleton piano assistance system for individuals recovering from neurological injuries, aiming to help users regain the ability to perform complex tasks such as…
Daniele Mortari, David Arnas
This work presents an initial analysis of using bijective mappings to extend the Theory of Functional Connections to non-rectangular two-dimensional domains. Specifically, this manuscript proposes three different mappings techniques: (a) complex mapping, (b) the projection mapping, and (c) polynomial mapping. In that…
Vencislav Popov, Markus Ostarek, Caitlin Tenison
A key challenge for cognitive neuroscience is to decipher the representational schemes of the brain. A recent class of decoding algorithms for fMRI data, stimulus-feature-based encoding models, is becoming increasingly popular for inferring the dimensions of neural representational spaces from stimulus-feature spaces.…
Judith Schmidt, Lilli Wollermann, Stephan Abele, Romy Müller + 1 more
Solving problems in a technical system usually requires people to understand its functioning on different levels of abstraction (i.e., goals, functions, components, characteristics) that are connected via means-ends links. We combined this abstraction hierarchy with concept mapping to assess people’s understanding of…
Chide Groenouwe, Jesse Nortier, John‐Jules Ch. Meyer
This paper presents a so-called maramafication of an essential part of functional programming languages such as Haskell or Clean: the construction of fully polymorphic well-typed algebraic data structures based on type definitions with at most one type parameter. As such, this work extends our previous work, in which…
John Gibbons, Shigeki Matsutani, Yoshihiro Ônishi
where ♮r is a certain multi-index of differentials. Here u1 and v1 are respectively the first components of u = w(P) and v = w(Q) which are given by the Abel map w : X → C g , where g is the genus of X. These explicit formulae are useful in applications, for instance to the problem of constructing classes of…
Philipp Rosenthal, Niels Demke, Frank Mantwill, Oliver Niggemann
The presented approach defines the decomposition problem in terms of a planning problem—a well established field in Artificial Intelligence. For the planning problem, logic-based solvers can be used to find solutions that compute a useful function structure for the design process. Well-known function libraries from…
Ichiroh Kanaya, Mayuko Kanazawa, Masataka Imura
This article presents the mathematical background of general interactive systems. The first principle of designing a large system is to "divide and conquer", which implies that we could possibly reduce human error if we divided a large system in smaller subsystems. Interactive systems are, however, often composed of…
Kyle Richardson
Recent work by (Richardson and Kuhn, 2017a,b; Richardson et al., 2018) looks at semantic parser induction and question answering in the domain of source code libraries and APIs. In this brief note, we formalize the representations being learned in these studies and introduce a simple domain specific language and a…
Carlos Schmidt, Friedrich Volz, Ljiljana Stojanovic, Gerhard Sutschet + 1 more
'Gerhard Sutschet' 'Yi Qin'] Although standards and specifications for digital twins aim to create interoperability in Industry 4.0, each standard has its own goals, focuses and representations for digital twins. This paper examines an approach to increasing interoperability between established digital twin…
Duncan Bossion, Sutirtha Chowdhury, Pengfei Huo
We present the rigorous theoretical framework of the generalized spin mapping representation for non- adiabatic dynamics. This formalism is based on the generators of the su(N) Lie algebra to represent N discrete electronic states, thus preserving the size of the original Hilbert space in the state representation. The…
Takayuki Hoshino, Suguru Kanoga, Atsushi Aoyama
Owing to pronounced inter-individual variability in biological signals, transfer learning has emerged as a widely used strategy to reduce calibration requirements for new users. Among the various approaches, style transfer mapping (STM) is distinguished by its ability to align the data distribution of target users…
Sabah Al‐Fedaghi
—Requirements engineering plays a critical role in developing software systems. One of the most difficult tasks in this process is identifying functional requirements. A critical problem in many projects is missing requirements until late in the development cycle. In this paper, our core interest is function modeling…
Oliver Struckmeier, Ievgen Redko, Anton Mallasto, Karol Arndt + 2 more
'Markus Heinonen' 'Ville Kyrki'] Optimal transport (OT) is a powerful geometric tool used to compare and align probability measures following the least effort principle. Despite its widespread use in machine learning (ML), OT problem still bears its computational burden, while at the same time suffering from the curse…
Viola Mocz, Maryam Vaziri-Pashkam, Marvin Chun, Yaoda Xu
In everyday life, we have no trouble recognizing and categorizing objects as they change in position, size, and orientation in our visual fields. This phenomenon is known as object invariance. Previous fMRI research suggests that higher-level object processing regions in the human lateral occipital cortex may link…
Authors not listed
Curried functions provide a systematic way of transforming multi-argument functions into nested singleargument functions. This transformation allows partial application and supports many central principles of functional programming. Their extension, called curried 𝑘-ary functions, naturally generalizes the familiar…
Tianfan Jin, Brett M Savoie
Contemporary machine learning algorithms have largely succeeded in automating the development of mathematical models from data. Although this is a striking accomplishment, it leaves unaddressed the multitude of scenarios, especially across the chemical sciences and engineering, where deductive, rather than inductive…
Ayush Pandey, Inigo Incer, Alberto Sangiovanni-Vincentelli, Richard M. Murray
We provide a new perspective on using formal methods to model specifications and synthesize implementations for the design of biological circuits. In synthetic biology, design objectives are rarely described formally. We present an assume-guarantee contract framework to describe biological circuit design objectives as…