Search Results for author: Thomas Heinis

Found 6 papers, 1 papers with code

Conditional Variational Diffusion Models

1 code implementation4 Dec 2023 Gabriel della Maggiora, Luis Alberto Croquevielle, Nikita Deshpande, Harry Horsley, Thomas Heinis, Artur Yakimovich

Despite their success, an important drawback of diffusion models is their sensitivity to the choice of variance schedule, which controls the dynamics of the diffusion process.

Super-Resolution

DNA Storage Error Simulator: A Tool for Simulating Errors in Synthesis, Storage, PCR and Sequencing

no code implementations28 May 2022 Jamie J. Alnasir, Thomas Heinis, Louis Carteron

Advances in DNA technologies have made it possible to store the entirety of Wikipedia in a test tube and read that information using a handheld sequencing device, although imperfections in writing (synthesis) and reading (sequencing) need to be mitigated for it to be viable as a mainstream storage medium.

DNA data storage, sequencing data-carrying DNA

no code implementations11 May 2022 Jasmine Quah, Omer Sella, Thomas Heinis

In this paper, we study accuracy trade-offs between deep model size and error correcting codes.

Model Compression

COAX: Correlation-Aware Indexing on Multidimensional Data with Soft Functional Dependencies

no code implementations29 Jun 2020 Ali Hadian, Behzad Ghaffari, Taiyi Wang, Thomas Heinis

The initial work on learned indexes has shown that by learning the cumulative distribution function of the data, index structures such as the B-Tree can improve their performance by one order of magnitude while having a smaller memory footprint.

Attribute

Hands-off Model Integration in Spatial Index Structures

no code implementations29 Jun 2020 Ali Hadian, Ankit Kumar, Thomas Heinis

Spatial indexes are crucial for the analysis of the increasing amounts of spatial data, for example generated through IoT applications.

Survey of Information Encoding Techniques for DNA

no code implementations24 Jun 2019 Thomas Heinis, Roman Sokolovskii, Jamie J. Alnasir

Whilst biological information is encoded in DNA via a specific mapping from triplet sequences of nucleotides to amino acids, DNA storage is not limited to a single encoding scheme, and there are many possible ways to map data to chemical sequences of nucleotides for synthesis, storage, retrieval and data manipulation.

Information Retrieval Retrieval

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