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Found 15 papers, 5 papers with code
Choose Your Own Question: Encouraging Self-Personalization in Learning Path Construction
Finally, Rocket provides students with fine-grained information on their learning path, giving them an avenue to assess their own skills and track their learning progress.
Lagrangian Neural Style Transfer for Fluids
Artistically controlling the shape, motion and appearance of fluid simulations pose major challenges in visual effects production.
Prescribing Deep Attentive Score Prediction Attracts Improved Student Engagement
To that end, we apply a state-of-the-art deep attentive neural network-based score prediction model to Santa, a multi-platform English ITS with approximately 780K users in South Korea that exclusively focuses on the TOEIC (Test of English for International Communications) standardized examinations.
Latent Space Subdivision: Stable and Controllable Time Predictions for Fluid Flow
By selectively overwriting parts of the predicted latent space points, our proposed method is capable to robustly predict long-term sequences of complex physics problems.
Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing
To the best of our knowledge, this is the first work to suggest an encoder-decoder model for knowledge tracing that applies deep self-attentive layers to exercises and responses separately.
Ranked #2 on
Knowledge Tracing
on EdNet
Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment
First, we define the concept of the study session, study session dropout and study session dropout prediction task in a mobile learning environment.
Frequency-Aware Reconstruction of Fluid Simulations with Generative Networks
Convolutional neural networks were recently employed to fully reconstruct fluid simulation data from a set of reduced parameters.
Neural Smoke Stylization with Color Transfer
Artistically controlling fluid simulations requires a large amount of manual work by an artist.
Graphics
EdNet: A Large-Scale Hierarchical Dataset in Education
With advances in Artificial Intelligence in Education (AIEd) and the ever-growing scale of Interactive Educational Systems (IESs), data-driven approach has become a common recipe for various tasks such as knowledge tracing and learning path recommendation.
Transport-Based Neural Style Transfer for Smoke Simulations
Optimization techniques rely on approximating simulation states towards target velocity or density field configurations, which are often handcrafted by artists to indirectly control smoke dynamics.
Robust Reference Frame Extraction from Unsteady 2D Vector Fields with Convolutional Neural Networks
In this paper, we utilize a convolutional neural network to combine two steps of the visualization pipeline in an end-to-end manner: the filtering and the feature extraction.
Graphics
Deep Fluids: A Generative Network for Parameterized Fluid Simulations
This paper presents a novel generative model to synthesize fluid simulations from a set of reduced parameters.
Automatic Open Knowledge Acquisition via Long Short-Term Memory Networks with Feedback Negative Sampling
To the best of our knowledge, this is the first work to apply deep learning to Open IE.
Accurate Localization of 3D Objects from RGB-D Data Using Segmentation Hypotheses
In this paper we focus on the problem of detecting objects in 3D from RGB-D images.
