Time Series

1049 papers with code • 2 benchmarks • 6 datasets

Time series deals with sequential data where the data is indexed (ordered) by a time dimension.

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

Latest papers with code

Crop Rotation Modeling for Deep Learning-Based Parcel Classification from Satellite Time Series

felixquinton1/deep-crop-rotation 15 Oct 2021

While annual crop rotations play a crucial role for agricultural optimization, they have been largely ignored for automated crop type mapping.

Classification Crop Classification +1

2
15 Oct 2021

FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes

rjbruin/flexconv 15 Oct 2021

In this work, we propose FlexConv, a novel convolutional operation with which high bandwidth convolutional kernels of learnable kernel size can be learned at a fixed parameter cost.

Sequential Image Classification Time Series

0
15 Oct 2021

Dynamical Wasserstein Barycenters for Time-series Modeling

kevin-c-cheng/dynamicalwassbarycenters_gaussian 13 Oct 2021

We propose a dynamical Wasserstein barycentric (DWB) model that estimates the system state over time as well as the data-generating distributions of pure states in an unsupervised manner.

Time Series

2
13 Oct 2021

Ousiometrics and Telegnomics: The essence of meaning conforms to a two-dimensional powerful-weak and dangerous-safe framework with diverse corpora presenting a safety bias

petersheridandodds/ousiometry 13 Oct 2021

We define `ousiometrics' to be the study of essential meaning in whatever context that meaningful signals are communicated, and `telegnomics' as the study of remotely sensed knowledge.

Artificial Life Time Series

0
13 Oct 2021

PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids

tamu-engineering-research/Open-source-power-dataset 12 Oct 2021

The electric grid is a key enabling infrastructure for the ambitious transition towards carbon neutrality as we grapple with climate change.

Time Series

1
12 Oct 2021

Chaos as an interpretable benchmark for forecasting and data-driven modelling

williamgilpin/dysts 11 Oct 2021

Our dataset is annotated with known mathematical properties of each system, and we perform feature analysis to broadly categorize the diverse dynamics present across the collection.

Time Series Time Series Classification +1

84
11 Oct 2021

TCube: Domain-Agnostic Neural Time-series Narration

Mandar-Sharma/TCube 11 Oct 2021

We present TCube (Time-series-to-text), a domain-agnostic neural framework for time-series narration, that couples the representation of essential time-series elements in the form of a dense knowledge graph and the translation of said knowledge graph into rich and fluent narratives through the transfer-learning capabilities of PLMs (Pre-trained Language Models).

Epidemiology Knowledge Graphs +3

6
11 Oct 2021

Graph-Guided Network for Irregularly Sampled Multivariate Time Series

mims-harvard/raindrop 11 Oct 2021

Here, we introduce RAINDROP, a graph-guided network for learning representations of irregularly sampled multivariate time series.

Time Series

2
11 Oct 2021

Long Expressive Memory for Sequence Modeling

tk-rusch/lem 10 Oct 2021

We propose a novel method called Long Expressive Memory (LEM) for learning long-term sequential dependencies.

Language Modelling Sequential Image Classification +3

5
10 Oct 2021

Topological Data Analysis (TDA) Techniques Enhance Hand Pose Classification from ECoG Neural Recordings

machinelearningjournalclub/ecog_vbh_2021 9 Oct 2021

With our method, we observed robust results in terms of ac-curacy for a four-labels classification problem, with limited available data.

Feature Importance Hyperparameter Optimization +3

3
09 Oct 2021