| 301. | Paper review - Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey | AISC | 47:26 | Review |
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| 302. | AI, Democracy, & Disinformation | 47:09 | Guide |
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| 303. | Hypothesis Generation with AGATHA : Accelerate Scientific Discovery with Deep Learning | AISC | 47:09 | |
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| 304. | Overview of Reinforcement Learning | AISC | 46:54 | |
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| 305. | Neural Search for Augmented Decision Making - Zeta Alpha - DRT S2E17 | 46:44 | Let's Play |
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| 306. | Explainable AI for Time Series - Literature Review | AISC | 46:44 | Review |
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| 307. | A Literature Review on ML in Health Care : Introducing new AISC Stream | AISC | 46:44 | Review |
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| 308. | LabDAO - Decentralized Marketplace for Research in Life Sciences - DRT S2E11 | 46:42 | |
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| 309. | Proving the Lottery Ticket Hypothesis: Pruning is All You Need | AISC Livestream with the Author | 46:31 | |
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| 310. | Subexponential-Time Algorithms for Sparse PCA | AISC | 46:27 | |
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| 311. | Screening and analysis of specific language impairment | AISC | 46:17 | |
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| 312. | Unifying machine learning and quantum chemistry with a deep neural network | AISC | 45:51 | |
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| 313. | Machine Learning in Cyber Security, Overview | AISC | 45:40 | |
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| 314. | Some Salient Issues with Saliency Models | AISC | 45:31 | |
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| 315. | Building (AI?) Products; Step by Step Guide | AISC | 45:25 | Guide |
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| 316. | TDLS: Learning Functional Causal Models with GANs - part 1 (algorithm review) | 45:24 | Review |
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| 317. | A Literature Review on Deep Learning in Finance | AISC | 45:22 | Review |
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| 318. | Generative AI: Ethics, Accessibility, Legal Risk Mitigation | 45:15 | |
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| 319. | Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods | AISC | 45:12 | |
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| 320. | Connectionist Temporal Classification, Labelling Unsegmented Sequence Data with RNN | TDLS | 44:58 | |
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| 321. | We Can Measure XAI Explanations Better with Templates | AISC | 44:52 | |
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| 322. | Getting into Reinforcement Learning - Fireside Chat | 44:44 | |
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| 323. | XAI with Monotonic Constraints & Interaction Constraints | 44:37 | |
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| 324. | RecSys, Reverse Engineering User's Needs and Desires | AISC | 44:35 | |
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| 325. | Integrating LLMs into Your Product: Considerations and Best Practices | 44:25 | |
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| 326. | Learning-free Controllable Text Generation for Debiasing | 44:18 | |
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| 327. | Similarity Search for Efficient Active Learning and Search of Rare Concepts | AISC | 44:13 | |
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| 328. | Survival regression with AFT model in XGBoost | AISC | 44:13 | |
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| 329. | Building and leveraging pragmatic AI solutions for legal services | AISC | 44:12 | |
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| 330. | Machine Learning in Environmental Science and Prediction: An Overview | AISC | 44:05 | |
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| 331. | [StyleGAN] A Style-Based Generator Architecture for GANs, part2 (results and discussion) | TDLS | 44:03 | Discussion |
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| 332. | Data exploration – can machine learning discover new drugs? | AISC | 43:48 | |
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| 333. | Which Open-source LLM to Choose for Your Task? | 43:24 | |
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| 334. | Embeddings of weather forecast images for search and more | 43:18 | |
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| 335. | Evaluating Performance of Large Language Models with Linguistics - Deep Random Talks S2E5 | 43:14 | |
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| 336. | Defining your AI Value Model for Product Success (and Profit) | AISC | 43:11 | |
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| 337. | (Original Paper) Latent Dirichlet Allocation (algorithm) | AISC Foundational | 43:11 | |
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| 338. | Expanding the Capabilities of Language Models with External Tools | 43:10 | |
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| 339. | Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning | AISC | 43:08 | |
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| 340. | A machine learning and informatics program package for modeling of chemical and materials data | AIS | 43:07 | |
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| 341. | BERTology Meets Biology: Interpreting Attention in Protein Language Models | AISC | 42:51 | Vlog |
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| 342. | Machine learning meets continuous flow chemistry: Automated process optimization | AISC | 42:50 | |
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| 343. | Inferring the 3D Standing Spine Posture from 2D Radiographs | AISC | 42:45 | |
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| 344. | Deep Learning in Healthcare and Its Practical Limitations | 42:32 | |
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| 345. | Extracting Biologically Relevant Latent Space from Cancer Transcriptomes \w VAEs(discussions) I AISC | 42:18 | Discussion |
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| 346. | Neural Ordinary Differential Equations - part 2 (results & discussion) | AISC | 42:05 | Discussion |
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| 347. | DeSci Labs: Creating A Backend For Scientific Papers - Deep Random Talks S2 E1 | 41:48 | |
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| 348. | Beyond Accuracy: Behavioral Testing of NLP Models with CheckList | AISC | 41:38 | Let's Play |
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| 349. | explainX - Explainable AI for model developers | AISC | 41:36 | |
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| 350. | Towards Frequency-Based Explanation for Robust CNN | AISC | 41:31 | |
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| 351. | Evaluation of Multimodal RAG Systems using the LlamaIndex | 41:27 | |
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| 352. | Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer | 41:25 | |
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| 353. | GrowNet: Gradient Boosting Neural Networks | AISC | 41:11 | |
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| 354. | Locality Guided Neural Networks for Explainable AI | AISC | 41:05 | Guide |
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| 355. | Running LLMs in Your Environment | 40:43 | |
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| 356. | Council: A Framework for Developing Generative AI Applications | 40:39 | |
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| 357. | Overview of Machine Learning in Behavioral Economics | AISC | 40:38 | |
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| 358. | A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosi | 40:21 | |
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| 359. | Discovering Symbolic Inductive Biases | AISC | 39:49 | |
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| 360. | COVID and Racial Inequity, and Implications for AI | 38:59 | |
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| 361. | Product Ideation: From a Hunch to a Concrete Idea | 38:54 | |
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| 362. | Building with LLMs Using LangChain | 38:28 | |
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| 363. | A Literature Review on Reinforcement Learning in Process Control | AISC | 38:23 | Review |
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| 364. | Modern NLP: Review of Transformers- Session 5 | 38:19 | Let's Play |
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| 365. | How to Track Objects in Videos with Self-supervised Techniques | AISC | 38:17 | Guide |
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| 366. | High Dimensional Inference in the Universe | 37:58 | |
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| 367. | Augmented Out-of-sample Comparison Method for Time Series Forecasting Techniques | AISC | 37:37 | |
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| 368. | The Business Impact and Challenges of Using Large Language Models | 37:20 | |
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| 369. | [BERT] Pretranied Deep Bidirectional Transformers for Language Understanding (discussions) | TDLS | 37:20 | Discussion |
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| 370. | LLM Starter Pack: A Pragmatic Guide to Success with the Large Language Models | 37:04 | |
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| 371. | Investigating Anti-Muslim Bias in GPT-3 | 36:47 | |
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| 372. | The AI Design Sprint -- setting your AI Initiative up for delivery success! | AISC | 36:46 | |
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| 373. | Automated Deep Learning: Joint Neural Architecture and Hyperparameter Search (discussions) | AISC | 36:42 | Discussion |
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| 374. | 'Less Than One'-Shot Learning (author speaking) | 36:32 | |
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| 375. | Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning | AISC | 36:22 | |
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| 376. | Generating Ampicillin-Level Antimicrobial Peptides with Activity-Aware Generative Adversarial Net | 36:08 | |
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| 377. | Automated Deep Learning: Joint Neural Architecture and Hyperparameter Search (algorithm) | AISC | 35:53 | |
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| 378. | Large Language Models as a Building Blocks | 35:34 | |
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| 379. | Machine Learning for Cyber Security - Session 11 | 35:33 | |
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| 380. | ChatGPT-like application for construction of mathematical financial models | 35:32 | |
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| 381. | Non-Euclidean Universal Approximation | AISC | 35:07 | |
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| 382. | Machine Learning Product Competitions - Winners' Roundtable Discussion | 35:02 | Discussion |
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| 383. | Wind Farm Generator Condition Monitoring | 34:50 | |
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| 384. | [T-Fixup] Improving Transformer Optimization Through Better Initialization | AISC | 34:47 | |
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| 385. | DLIME - Let's dig into the code (model explainability stream) | 34:39 | |
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| 386. | Few-Shot Learning Through an Information Retrieval Lens | TDLS | 34:38 | Guide |
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| 387. | [FFJORD] Free-form Continuous Dynamics for Scalable Reversible Generative Models (Part 1) | AISC | 34:26 | |
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| 388. | LLMs for Security Compliance Assessment | 33:57 | |
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| 389. | Commercializing LLMs: Lessons and Ideas for Agile Innovation | 33:35 | |
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| 390. | Representation Learning of Histopathology Images using Graph Neural Networks | AISC | 33:28 | Vlog |
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| 391. | Leveraging Language Models for Training Data Generation and Tool Learning | 33:21 | |
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| 392. | (Original Paper) Latent Dirichlet Allocation (discussions) | AISC Foundational | 32:41 | Discussion |
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| 393. | TDLS: Learning Functional Causal Models with GANs - part 2 (results and discussion) | 32:30 | Discussion |
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| 394. | Practical Applications, Impact, and ROI of Generative AI | 32:20 | |
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| 395. | TDLS: Large-Scale Unsupervised Deep Representation Learning for Brain Structure | 32:08 | |
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| 396. | LLM Products for Regulated Industries | 31:40 | |
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| 397. | Incorporating Large Language Models into Enterprise Analytics | 31:36 | |
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| 398. | Role of Human Factors in Adoption of Generative AI in Life Sciences | 31:29 | |
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| 399. | Massive acceleration by using neural networks to emulate mechanism-based biological models | 31:24 | Vlog |
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| 400. | A Literature Review on Machine Learning in Materials Science | AISC | 31:19 | Review |
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