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Found 12 papers, 0 papers with code
Continuous Time Continuous Space Homeostatic Reinforcement Learning (CTCS-HRRL) : Towards Biological Self-Autonomous Agent
Homeostasis is a biological process by which living beings maintain their internal balance.
Long-Term Ad Memorability: Understanding and Generating Memorable Ads
Finally, with the intent of memorable ad generation, we present a scalable method to build a high-quality memorable ad generation model by leveraging automatically annotated data.
Probing Semantic Grounding in Language Models of Code with Representational Similarity Analysis
In this paper, we propose using Representational Similarity Analysis to probe the semantic grounding in language models of code.
ML-Based Analysis to Identify Speech Features Relevant in Predicting Alzheimer's Disease
Confusion matrices and feature importance graphs have been plotted model-wise to compare the performances of our models.
Deep Neural Networks on EEG Signals to Predict Auditory Attention Score Using Gramian Angular Difference Field
In this paper, we focus on this very problem of estimating a person's auditory attention level based on their brain's electrical activity captured using 14-channeled EEG signals.
Deep Neural Networks on EEG signals to predict Attention Score using Gramian Angular Difference Field
In this paper, we focus on this very problem of estimating a person's auditory attention level based on their brain's electrical activity captured using 14-channeled EEG signals.
Alzheimers Dementia Detection using Acoustic & Linguistic features and Pre-Trained BERT
Alzheimers disease is a fatal progressive brain disorder that worsens with time.
Wheelchair automation by a hybrid BCI system using SSVEP and eye blinks
Herein a working prototype of a BCI-based wheelchair is detailed that can navigate inside a typical home environment with minimum structural modification and without any visual obstruction and discomfort to the user.
Towards Using Diachronic Distributed Word Representations as Models of Lexical Development
Our experiments demonstrate the ease of usage and effectiveness of diachronic distributed word representations in modeling lexical development.
Vyākarana: A Colorless Green Benchmark for Syntactic Evaluation in Indic Languages
We use the datasets from the evaluation tasks to probe five multilingual language models of varying architectures for syntax in Indic languages.
Reinforcement Learning and its Connections with Neuroscience and Psychology
In this paper, we comprehensively review a large number of findings in both neuroscience and psychology that evidence reinforcement learning as a promising candidate for modeling learning and decision making in the brain.
CNRL at SemEval-2020 Task 5: Modelling Causal Reasoning in Language with Multi-Head Self-Attention Weights based Counterfactual Detection
We use pre-trained transformer models to extract contextual embeddings and self-attention weights from the text.
