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Found 23 papers, 13 papers with code
One of these words is not like the other: a reproduction of outlier identification using non-contextual word representations
The data set is expanded to contain semantic and syntactic tests and is multilingual (English, German, and Italian).
Multi-Source Temporal Attention Network for Precipitation Nowcasting
Precipitation nowcasting is crucial across various industries and plays a significant role in mitigating and adapting to climate change.
Temporal Subspace Clustering for Molecular Dynamics Data
We introduce MOSCITO (MOlecular Dynamics Subspace Clustering with Temporal Observance), a subspace clustering for molecular dynamics data.
Measuring and Benchmarking Large Language Models' Capabilities to Generate Persuasive Language
As opposed to prior work which focuses on particular domains or types of persuasion, we conduct a general study across various domains to measure and benchmark to what degree LLMs produce persuasive language - both when explicitly instructed to rewrite text to be more or less persuasive and when only instructed to paraphrase.
Wiki Entity Summarization Benchmark
Additionally, WikES features a dataset generator to test entity summarization algorithms in different areas of the knowledge graph.
RainAI -- Precipitation Nowcasting from Satellite Data
This paper presents a solution to the Weather4Cast 2023 competition, where the goal is to forecast high-resolution precipitation with an 8-hour lead time using lower-resolution satellite radiance images.
ActUp: Analyzing and Consolidating tSNE and UMAP
tSNE and UMAP are popular dimensionality reduction algorithms due to their speed and interpretable low-dimensional embeddings.
GiDR-DUN; Gradient Dimensionality Reduction -- Differences and Unification
In this work, we show that this is indeed possible by combining the two approaches into a single method.
Generalized Classification of Satellite Image Time Series with Thermal Positional Encoding
Unlike previous positional encoding based on calendar time (e. g. day-of-year), TPE is based on thermal time, which is obtained by accumulating daily average temperatures over the growing season.
Weakly-Supervised Cloud Detection with Fixed-Point GANs
Convolutional neural networks (CNNs) have greatly advanced the state-of-the-art in the detection of clouds in satellite images, but existing CNN-based methods are costly as they require large amounts of training images with expensive pixel-level cloud labels.
TimeMatch: Unsupervised Cross-Region Adaptation by Temporal Shift Estimation
However, when applied to target regions spatially different from the training region, these models perform poorly without any target labels due to the temporal shift of crop phenology between regions.
On Quantitative Evaluations of Counterfactuals
As counterfactual examples become increasingly popular for explaining decisions of deep learning models, it is essential to understand what properties quantitative evaluation metrics do capture and equally important what they do not capture.
Learning by Design: Structuring and Documenting the Human Choices in Machine Learning Development
The influence of machine learning (ML) is quickly spreading, and a number of recent technological innovations have applied ML as a central technology.
ECINN: Efficient Counterfactuals from Invertible Neural Networks
Counterfactual examples identify how inputs can be altered to change the predicted class of a classifier, thus opening up the black-box nature of, e. g., deep neural networks.
A reproduction of Apple's bi-directional LSTM models for language identification in short strings
Language Identification is the task of identifying a document's language.
Ranked #1 on
Language Identification
on OpenSubtitles
Accelerated High-Quality Mutual-Information Based Word Clustering
We present efficient implementations of Brown clustering and the alternative Exchange clustering as well as a number of methods to accelerate the computation of both hierarchical and flat clusters.
A Real-World Data Resource of Complex Sensitive Sentences Based on Documents from the Monsanto Trial
In this work we present a corpus for the evaluation of sensitive information detection approaches that addresses the need for real world sensitive information for empirical studies.
Active Learning of SVDD Hyperparameter Values
Existing methods to estimate hyperparameter values are purely heuristic, and the conditions under which they work well are unclear.
Abbreviation Explorer - an interactive system for pre-evaluation of Unsupervised Abbreviation Disambiguation
We present Abbreviation Explorer, a system that supports interactive exploration of abbreviations that are challenging for Unsupervised Abbreviation Disambiguation (UAD).
Quantifying the morphosyntactic content of Brown Clusters
We show that increases in Average Mutual Information, the clustering algorithms{'} optimization goal, are highly correlated with improvements in encoding of morphosyntactic information.
Unsupervised Abbreviation Disambiguation Contextual disambiguation using word embeddings
In this paper, we present an entirely unsupervised abbreviation disambiguation method (called UAD) that picks up abbreviation definitions from unstructured text.
Abbreviation Expander - a Web-based System for Easy Reading of Technical Documents
Abbreviations and acronyms are a part of textual communication in most domains.
Learning Representations for Outlier Detection on a Budget
We demonstrate the good performance of BORE compared to a variety of competing methods in the non-budgeted and the budgeted outlier detection problem on 12 real-world datasets.
