24 papers · ranked by Valyu relevance
Chanchan Xu, Gang Yang, Meng Yang, RunGuo Zang
In constructing and visualizing a virtual three-dimensional forest scene, we must first obtain the vegetation distribution, namely, the location of each plant in the forest. Because the forest contains a large number of plants, the distribution of each plant is difficult to obtain from actual measurement methods.…
Krzysztof M. Nowak, Robert E. Przekop, Stefano Mariani
Highlights 1. Automated “data factory” is one of the solutions to the data starvation problem in AI-driven discovery of polymers and composites. 2. Robotic platforms with in-line rheology produce thousands of standardized material variants annually at low cost. 3. Continuous Material Management with physical tagging…
Manuel Moussallam, Antoine Liutkus, Laurent Daudet
This work explores nonparametric methods which aim at synthesizing audio from low-dimensionnal acoustic features typically used in MIR frameworks. Several issues prevent this task to be straightforwardly achieved. Such features are designed for analysis and not for synthesis, thus favoring high-level description over…
Fred Bruford, Frederik Blang, Shahan Nercessian
Systems for synthesizer sound matching, which automatically set the parameters of a synthesizer to emulate an input sound, have the potential to make the process of synthesizer programming faster and easier for novice and experienced musicians alike, whilst also affording new means of interaction with synthesizers.…
Eli N. Weinstein, Alan N. Amin, Will Grathwohl, Daniel Kassler + 2 more
Generative probabilistic models of biological sequences have widespread existing and potential applications in analyzing, predicting and designing proteins, RNA and genomes. To test the predictions of such a model experimentally, the standard approach is to draw samples, and then synthesize each sample individually in…
Eli N. Weinstein, Mattia G. Gollub, Andrei Slabodkin, Cameron L. Gardner + 5 more
We introduce a method to reduce the cost of synthesizing proteins and other biological sequences designed by a generative model by as much as a trillion-fold. In particular, we make our generative models manufacturing-aware, such that model-designed sequences can be efficiently synthesized in the real world with…
Lamtharn Hantrakul, Li-Chia Yang
WaveNet, a deep neural network architecture for speech and audio generation, has brought exciting innovations in the sound domain since its introduction in 2016 [2]. In the musical domain, WaveNet has been used as an auto-encoder capable of interpolating – or non-linear "blending" – different instrument sounds through…
Siqin Peng, Xi Chen, Guanhua Wu, Ming Li + 2 more
'Angelos Filippatos'] Because of the high cost of experimental data acquisition, the limited size of the sample set available when conducting tissue structure ultrasound evaluation can cause the evaluation model to have low accuracy. To address such a small-sample problem, the sample set size can be expanded by using…
Nayeon Kim, Hyuk Jun Yoo, Daeho Kim, Heeseung Lee + 1 more
Autonomous laboratories hold great promise for accelerating material discovery but are often restricted by static, predefined experimental constraints. We present SPACESHIP, an AIdriven framework for dynamic, constraint-free exploration of synthesizable regions in chemical parameter spaces. SPACESHIP integrates…
Zhe Zhang, Taketo Akama
GANStrument, exploiting GANs with a pitch-invariant feature extractor and instance conditioning technique, has shown remarkable capabilities in synthesizing realistic instrument sounds. To further improve the reconstruction ability and pitch accuracy to enhance the editability of user-provided sound, we propose…
Jacob T. Rapp, Bennett J. Bremer, Philip A. Romero
Protein engineering has nearly limitless applications across chemistry, energy and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive and inefficient. Here we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for fully…
Xiandi Zhang, Xianger Jiang, Yun Wang, Qinzhen Chen + 25 more
DNA synthesis serves as the fundamental enabling technology of engineering biology, aiming to provide DNA molecules of designed composition, length, and complexity at scale and low cost. Current high-throughput DNA synthesis technologies rely on intricate chip manufacturing and microfluidic systems to provide…
Gerhard Widmer, Maarten Grachten, Stefan Lattner
> Abstract We introduce a method for imposing higher-level structure on generated, polyphonic music. A Convolutional Restricted Boltzmann Machine (C-RBM) as a generative model is combined with gradient descent constraint optimisation to provide further control over the generation process. Among other things, this…
Jeff Guo, Philippe Schwaller
Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy desired objectives under minimal oracle evaluations (computational prediction or wet-lab experiment). This problem becomes more apparent when using oracles that can provide increased…
Jacob T. Rapp, Bennett J. Bremer, Philip A. Romero
Protein engineering has nearly limitless applications across chemistry, energy, and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive, and inefficient. In this work, we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for…
David Nečas, Petr Klapetek, Linda J. Johnston
Synthetic data are of increasing importance in nanometrology. They can be used for development of data processing methods, analysis of uncertainties and estimation of various measurement artefacts. In this paper we review methods used for their generation and the applications of synthetic data in scanning probe…
Ben J. Hayes, Charalampos Saitis, György Fazekas
Many audio synthesizers can produce the same signal given different parameter configurations, meaning the inversion from sound to parameters is an inherently ill-posed problem. We show that this is largely due to intrinsic symmetries of the synthesizer, and focus in particular on permutation invariance. First, we…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
Megan Stanley, Marwin Segler
Computational techniques, including virtual screening, de novo design, and generative models, play an increasing role in expediting DMTA cycles for modern molecular discovery. However, computationally proposed molecules must be synthetically feasible for laboratory testing. In this perspective, we offer a succinct…
Authors not listed
Computer-aided synthesis planning aims to identify viable synthetic routes from a target compound to readily available building blocks by iteratively decomposing molecules into smaller precursors. Self-play search algorithms, trained with simulated experience, reach state-of-the-art performance. However, these methods…
Andre KY Low, Flore Mekki-Berrada, Aleksandr Ostudin, Jiaxun Xie + 7 more
The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental design. When solving optimization problems, Bayesian-based optimizers are often…
Zhen Ye, Wei Xue, Xu Tan, Qifeng Liu + 1 more
Developing digital sound synthesizers is crucial to the music industry as it provides a low-cost way to produce high-quality sounds with rich timbres. Existing traditional synthesizers often require substantial expertise to determine the overall framework of a synthesizer and the parameters of submodules. Since expert…
Tarun Khajuria, Kadi Tulver, Jaan Aru
Human vision is not merely a passive process of interpreting sensory input but can also function as a problem-solving process incorporating generative mechanisms to interpret ambiguous or noisy data. This synergy between the generative and discriminative components, often described as analysis-by-synthesis, enables…
Zhimian Hao, Chonghuan Zhang, Alexei Lapkin
We propose a workflow for reduction in the time required for data generation during generation of statistical digital twins. This methodology is particularly relevant for real-world engineering problems when data generation is expensive. A prerequisite for building surrogates is sufficient input/output data, whereas…