| 201. | Evidential Reasoning Rule Based Feature Selection | AISC | 56:45 | |
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| 202. | Deep Learning for Symbolic Mathematics | AISC | 56:39 | |
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| 203. | Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities | AISC | 56:33 | |
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| 204. | The Synthesizability of Molecules Proposed by Generative Models | AISC | 56:32 | |
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| 205. | Machine Learning to Assess Trends and Alignment of Funded Research Output | AISC | 56:31 | |
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| 206. | Human-Machine Learning Systems: The Sum is Bigger than the Parts (with Professor Matthew Taylor) | 56:29 | |
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| 207. | Community-Driven Product Development - Deep Random Talk S2E3 | 56:25 | |
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| 208. | Human Aware AI: Reducing Transportation Energy of a City by Influencing Individual Behaviour | 56:25 | |
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| 209. | Policy Priority Inference: Simulations for Government Strategy | AISC | 56:24 | |
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| 210. | Learning to Play Soccer by Reinforcement Learning | AISC | 56:23 | |
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| 211. | Machine Learning Methods for High Throughput Virtual Screening with a focus on Organic Photovoltaics | 56:21 | |
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| 212. | Overview of Bias and Fairness in AI | 56:17 | |
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| 213. | Integrating Privacy is Integrating Ethics: What privacy could have done for Clearview AI | AISC | 56:14 | |
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| 214. | Cognitive Model Priors for Predicting Human Decisions | AISC | 56:03 | |
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| 215. | Battery Modelling using Data-Driven Machine Learning | AISC | 55:55 | |
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| 216. | Prediction of Cardiac arrest from physiological signals in the pediatric ICU | TDLS Author Speaking | 55:48 | Vlog |
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| 217. | COVID19 and AI: Ethics and Data Rights Panel | AISC & NYAI | 55:39 | Discussion |
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| 218. | [GATA] Learning Dynamic Belief Graphs to Generalize on Text-Based Games | AISC | 55:30 | |
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| 219. | Conceptual understanding through efficient inverse-design of quantum optical experiments | AISC | 55:29 | |
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| 220. | BottleSum: Unsupervised & Self-supervised Sentence Summarization w/ Information Bottleneck Principle | 55:28 | Guide |
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| 221. | Exploring the agency limits of today's LLMs | 55:25 | |
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| 222. | Investing in Deep Tech - Investor's Angle; Deep Random Talks S2E8 - Ft. Moien Giashi, Amir Feizpour | 55:24 | |
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| 223. | [hgraph2graph] Hierarchical Generation of Molecular Graphs using Structural Motifs | AISC Spotlight | 55:23 | |
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| 224. | Explainable AI with Layer-wise Relevance Propagation (LRP) | 55:19 | |
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| 225. | A Literature Review on ML in Climate Science | AISC | 55:16 | Review |
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| 226. | Multi-Armed Bandit Strategies for Non-Stationary Reward Distributions and Delayed Feedback Processes | 55:16 | |
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| 227. | Integrating Physics into Machine Learning Models for Scientific Discovery | AISC | 55:14 | |
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| 228. | Computational Thinking | 55:09 | |
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| 229. | Improving Supervised Bilingual Mapping of Word Embeddings | TDLS | 55:05 | |
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| 230. | Human-Technology Systems for Intelligent Civil Infrastructure Operation and Maintenance | AISC | 54:59 | Vlog |
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| 231. | Dealing with Bias and Fairness in Data Science Systems: A Practical Hands-on Tutorial | AISC | 54:50 | Preview |
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| 232. | Author speaking: Proper Machine Learning Explanations through LIME using OptiLIME framework | AISC | 54:44 | |
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| 233. | Knowledge Extraction from Multimodal & Multilingual sources | AISC | 54:36 | |
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| 234. | An Introduction to the Quantum Tech Ecosystem | AISC | 54:27 | |
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| 235. | [Author speaking] Protein docking model evaluation by 3D convolutional neural networks | AISC | 54:24 | |
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| 236. | Mathematics of Deep Learning Overview | AISC Lunch & Learn | 54:20 | |
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| 237. | Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches | | 54:18 | |
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| 238. | Attention is not not explanation + Character Eyes: Seeing Language through Character-Level Taggers | | 54:16 | |
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| 239. | [Transformer] Attention Is All You Need | AISC Foundational | 54:13 | |
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| 240. | Quantifying the dynamics of failure across science, startups and security | AISC | 54:13 | |
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| 241. | Disparate Interactions: An Algorithms-in-the-loop Analysis of Fairness in Risk Assessment | AISC | 54:11 | |
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| 242. | Tobias Pfaff (DeepMind): Learning to Simulate Complex Physics with Graph Networks | 54:04 | |
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| 243. | Overview of Unsupervised & Semi-supervised learning | AISC | 54:02 | |
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| 244. | Overview of Machine Learning for Knowledge Graphs | AISC | 53:43 | |
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| 245. | News Recommender System Considering Temporal Dynamics and News Taxonomy | AISC | 53:36 | |
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| 246. | NLP on Noisy User-generated text - NER for StackOverflow | AISC | 53:35 | Let's Play |
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| 247. | Meta-Graph: Few-Shot Link Prediction Using Meta-Learning | AISC | 53:31 | |
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| 248. | Overview of Modern Anomaly and Novelty Detection | AISC | 53:17 | |
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| 249. | [BERT] Pretranied Deep Bidirectional Transformers for Language Understanding (algorithm) | TDLS | 53:07 | |
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| 250. | [MEM] Learning Permutation Invariant Representations using Memory Networks | AISC | 53:04 | |
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| 251. | Navigating the Idea Maze: Continuous discovery frameworks for (AI?) products | AISC | 53:00 | |
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| 252. | Modern Knowledge Management in 2022 - Deep Random Talks S2E7 | 52:51 | |
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| 253. | Joint Policy-Value Learning for Recommendation | AISC | 52:33 | |
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| 254. | What is Wrong with Explainable AI? | AISC | 52:18 | |
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| 255. | Overview of Synthetic Data and Simulations | AISC | 52:16 | |
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| 256. | Identifying Influential Individuals in Complex Networks: An Overview | AISC | 52:10 | |
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| 257. | De-identification of patients’ protected health information (PHI) from medical free-text | AISC | 52:09 | Guide |
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| 258. | Dirichlet Pruning for Neural Network Compression | AISC | 51:57 | |
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| 259. | Nodes, Edges and Properties; Graph Analysis Intro for ML Newcomers | 51:57 | |
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| 260. | Application of Bayesian neural networks for aircraft safety | AISC | 51:42 | |
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| 261. | Highly Recommended: A Fireside Chat with AISC's Resident Experts on Recommender Systems | 51:35 | |
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| 262. | Quantum generative adversarial networks | TDLS Author Speaking | 51:26 | |
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| 263. | Meet the MLOps Experts, a fireside chat for newcomers to AI careers | 51:16 | |
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| 264. | AISC Abstract Night | 51:06 | |
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| 265. | TF-Encrypted: Private machine learning in tensorflow with secure computing | AISC Lunch & Learn | 50:50 | |
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| 266. | Layerwise Learning for Quantum Neural Networks | AISC | 50:47 | |
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| 267. | DrWhy.AI - Tools for Explainable Artificial Intelligence | AISC | 50:46 | |
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| 268. | LLMs in Production - A Costly Dilemma! | 50:45 | |
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| 269. | Topological Deep Learning | 50:31 | Vlog |
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| 270. | EVE - Explainable Vector Embeddings - DRT S2E12 | 50:30 | |
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| 271. | Building a better climate model with Machine Learning | AISC | 50:29 | |
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| 272. | Should ensemble members be calibrated? | AISC | 50:24 | |
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| 273. | [cnvrg.io] Operating System for Machine Learning | AISC | 50:18 | |
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| 274. | BillionX acceleration using AI Emulators | AISC | 50:08 | |
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| 275. | Second Brain for Technical Knowledge Management- DRT S2 E4 | 49:59 | |
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| 276. | Camera Depth of Field Manipulation for Pre- and Post-Image Capture | AISC | 49:50 | |
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| 277. | Data-Driven Behavior Change and Personalization - DRT S2E10 | 49:33 | |
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| 278. | End to end recommender engine using Amazon Glue and SageMaker - Use Case for Data Scientists | AISC | 49:24 | |
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| 279. | Targeted Machine Learning for Data Science | AISC | 49:22 | |
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| 280. | A Literature Review on Graph Neural Networks | 49:10 | Review |
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| 281. | A Literature Review on Interpretability for Machine Learning | AISC | 49:09 | Review |
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| 282. | Breaking Speed Limits with Simultaneous Ultra-Fast MRI Reconstruction and Tissue Segmentation | AISC | 49:09 | |
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| 283. | Distributed Data Engineering for Science - OpSci - Holonym - DRT S2E16 | 49:02 | |
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| 284. | Invest in Deep Tech like an Engineer - Deep Random Talks | 48:57 | |
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| 285. | [MOREL] Unsupervised Video Object Segmentation for Deep Reinforcement Learning | 48:56 | |
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| 286. | Data Structure for Knowledge = Language Models + Structured Data - DRT S2E13 | 48:54 | |
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| 287. | SELFIES: A 100% robust representation of semantically constrained Graphs, for deep generative models | 48:51 | |
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| 288. | Information Retrieval for Price Consistency Monitoring - Liu Yang (Amazon) | 48:45 | Guide |
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| 289. | Serina Chang: Understanding the spread of COVID-19 using Social Network Models | 48:36 | |
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| 290. | Founders in Fundraising, and AI Applications | 48:35 | |
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| 291. | Operationalizing the AI Canvas for AI Product Success (and profit) | AISC | 48:22 | |
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| 292. | ChatGPT - the Chatbot that Follows Instructions - DRT S2E9 | 48:13 | Tutorial |
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| 293. | Deep learning interpretation of echocardiograms | AISC | 48:12 | |
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| 294. | Modeling Dissolution of Compact Planetary Systems | 48:09 | |
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| 295. | DeepFakes & Explainable AI Applications in NLP, Biomedical & Malware Classification | 47:58 | |
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| 296. | Statistical Issues in Agent-Based Models | AISC | 47:58 | |
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| 297. | Unfolding the Maze of Funding Deep Tech; Metafold - DRT S2E14 - Ft. Moien Giashi, Alissa ross | 47:58 | |
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| 298. | Explainable Classifiers Using Counterfactual Approach | AISC | 47:46 | |
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| 299. | Explainable AI to Automate Loan Underwriting Decisions | AISC | 47:41 | |
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| 300. | Computer vision to deeply phenotype human diseases across physiological, tissue and molecular scales | 47:29 | Vlog |
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