Databricks TAO (Test-time Adaptive Optimization): The more your LLM is used, the better it can get!
Shayan Fazeli
Databricks TAO (Test-time Adaptive Optimization): The more your LLM is used, the better it can get!
5:44
PaperView: "ProbTS: A Unified Toolkit to Probe Deep Time-series Forecasting"
Shayan Fazeli
PaperView: "ProbTS: A Unified Toolkit to Probe Deep Time-series Forecasting"
34:55
Frechet Inception Distance and Inception Score - AI Bits and Pieces
Shayan Fazeli
Frechet Inception Distance and Inception Score - AI Bits and Pieces
19:28
ML in 2 Paper: Counterfactual Explanations for Graph Classification Through the Lenses of Density
Shayan Fazeli
ML in 2 Paper: Counterfactual Explanations for Graph Classification Through the Lenses of Density
5:55
ML in 2 Paper: LLMZip - Lossless Text Compression using Large Language Models
Shayan Fazeli
ML in 2 Paper: LLMZip - Lossless Text Compression using Large Language Models
3:07
ML in 2 Paper: Utterance Classification with LNNs - Explainable AI for Mental Disorder Diagnosis
Shayan Fazeli
ML in 2 Paper: Utterance Classification with LNNs - Explainable AI for Mental Disorder Diagnosis
2:12
ML in 2 Paper: TabR - Unlocking the Power of Retrieval-Augmented Tabular Deep Learning
Shayan Fazeli
ML in 2 Paper: TabR - Unlocking the Power of Retrieval-Augmented Tabular Deep Learning
3:21
ML in 2 Paper: Fine-grained visual prompting
Shayan Fazeli
ML in 2 Paper: Fine-grained visual prompting
3:22
ML in 2 Paper: FinGPT: Open-Source Financial Large Language Models
Shayan Fazeli
ML in 2 Paper: FinGPT: Open-Source Financial Large Language Models
1:47
ML in 2 Paper: CM3Leon Scaling Autoregressive Multi-Modal Models
Shayan Fazeli
ML in 2 Paper: CM3Leon Scaling Autoregressive Multi-Modal Models
7:23
ML in 2 Paper: Layer-level activation mechanism
Shayan Fazeli
ML in 2 Paper: Layer-level activation mechanism
2:23
ML in 2 Paper: Transformers as Statisticians - Provable In-Context Learning with Algorithm Selection
Shayan Fazeli
ML in 2 Paper: Transformers as Statisticians - Provable In-Context Learning with Algorithm Selection
2:51
ML in 2 Paper: PromptBench - Towards Evaluating the Robustness of Large Language Models
Shayan Fazeli
ML in 2 Paper: PromptBench - Towards Evaluating the Robustness of Large Language Models
2:34
ML in 2 Paper: ChatGPT is fun, but it is not funny! Humor is still challenging Large Language Models
Shayan Fazeli
ML in 2 Paper: ChatGPT is fun, but it is not funny! Humor is still challenging Large Language Models
2:23
ML in 2 Paper: BiomedGPT - A Unified and Generalist Biomedical Generative Pre-trained Transformer...
Shayan Fazeli
ML in 2 Paper: BiomedGPT - A Unified and Generalist Biomedical Generative Pre-trained Transformer...
2:29
ML in 2 Paper: Bytes Are All You Need: Transformers Operating Directly On File Bytes
Shayan Fazeli
ML in 2 Paper: Bytes Are All You Need: Transformers Operating Directly On File Bytes
2:35
ML in 2: Introduction
Shayan Fazeli
ML in 2: Introduction
1:16
ML in 2 Paper: Fine tuning language models with just forward passes"
Shayan Fazeli
ML in 2 Paper: Fine tuning language models with just forward passes"
2:17
PaperView: MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers
Shayan Fazeli
PaperView: MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers
32:00
On Meta Learning: Learning "learning to learn"
Shayan Fazeli
On Meta Learning: Learning "learning to learn"
50:25
PaperView: "Toolformer: Language models can teach themselves to use tools"
Shayan Fazeli
PaperView: "Toolformer: Language models can teach themselves to use tools"
36:37
PaperQA
Shayan Fazeli
PaperQA
33:04
PaperView: "When Are Graph Neural Networks Better Than Structure-Agnostic Methods?"
Shayan Fazeli
PaperView: "When Are Graph Neural Networks Better Than Structure-Agnostic Methods?"
22:36
Pytorch 2.0: An overview of what's new
Shayan Fazeli
Pytorch 2.0: An overview of what's new
11:32
PaperView: "Deep learning on a data diet"
Shayan Fazeli
PaperView: "Deep learning on a data diet"
21:34
PaperView: "Mish - A self-regulated non-monotonic activation function"
Shayan Fazeli
PaperView: "Mish - A self-regulated non-monotonic activation function"
19:55
PaperView: "Self-supervised multi-modal alignment for whole body medical imaging"
Shayan Fazeli
PaperView: "Self-supervised multi-modal alignment for whole body medical imaging"
12:45
Restricted Boltzmann Machines - AI Bits and Pieces
Shayan Fazeli
Restricted Boltzmann Machines - AI Bits and Pieces
8:09
Probability Bounds - AI Bits and Pieces
Shayan Fazeli
Probability Bounds - AI Bits and Pieces
32:16
PaperView: "CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback"
Shayan Fazeli
PaperView: "CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback"
21:19
A Quick Look at Optimal Transport - AI Bits and Pieces
Shayan Fazeli
A Quick Look at Optimal Transport - AI Bits and Pieces
11:57
PaperView: Denoising diffusion probabilistic models
Shayan Fazeli
PaperView: Denoising diffusion probabilistic models
1:00:12
PaperView: "On the Importance of Text Analysis for Stock Price Prediction"
Shayan Fazeli
PaperView: "On the Importance of Text Analysis for Stock Price Prediction"
8:22
PaperView: "Learning to Learn from Noisy Labeled Data"
Shayan Fazeli
PaperView: "Learning to Learn from Noisy Labeled Data"
10:24
PaperView: "Which strategies matter for noisy label classification? Loss and Uncertainty"
Shayan Fazeli
PaperView: "Which strategies matter for noisy label classification? Loss and Uncertainty"
9:54
PaperView: "Coverage-centric Coreset Selection for High Pruning Rates"
Shayan Fazeli
PaperView: "Coverage-centric Coreset Selection for High Pruning Rates"
18:35
PaperView: "Student Specialization in Deep ReLU Networks"
Shayan Fazeli
PaperView: "Student Specialization in Deep ReLU Networks"
1:45:42
PaperView: "Sample Selection for Fair and Robust Training"
Shayan Fazeli
PaperView: "Sample Selection for Fair and Robust Training"
20:12
PaperView: "Part-dependent Label Noise: Towards Instance-dependent Label Noise"
Shayan Fazeli
PaperView: "Part-dependent Label Noise: Towards Instance-dependent Label Noise"
15:50
PaperView: "Adversarial filters of dataset biases"
Shayan Fazeli
PaperView: "Adversarial filters of dataset biases"
18:44
PaperView: Predicting Social Anxiety from GPS Traces of College Students - Feasibility Study
Shayan Fazeli
PaperView: Predicting Social Anxiety from GPS Traces of College Students - Feasibility Study
14:03
PaperView: Learn by Challenging Yourself Contrastive Learning with Hard Sample Generation
Shayan Fazeli
PaperView: Learn by Challenging Yourself Contrastive Learning with Hard Sample Generation
14:07
PaperView: Learning classifiers from only positive and unlabeled data
Shayan Fazeli
PaperView: Learning classifiers from only positive and unlabeled data
19:25
PaperView: Neural manifold clustering and embedding
Shayan Fazeli
PaperView: Neural manifold clustering and embedding
25:18
PaperView - Mask R-CNN
Shayan Fazeli
PaperView - Mask R-CNN
10:49
PaperView: "Gradient Harmonized Single Stage Detector"
Shayan Fazeli
PaperView: "Gradient Harmonized Single Stage Detector"
15:58
PaperView: "Mask Scoring R CNN"
Shayan Fazeli
PaperView: "Mask Scoring R CNN"
12:17
PaperView: "Meta Pseudo Labels"
Shayan Fazeli
PaperView: "Meta Pseudo Labels"
11:58
PaperView - "Pay attention to MLPs"
Shayan Fazeli
PaperView - "Pay attention to MLPs"
19:41
0 - Graph Representation Learning Book - Preface
Shayan Fazeli
0 - Graph Representation Learning Book - Preface
0:45
2.3 - Graph Representation Learning Book - Chapter 2 [Part 3]
Shayan Fazeli
2.3 - Graph Representation Learning Book - Chapter 2 [Part 3]
40:23
2.2 - Graph Representation Learning Book - Chapter 2 [Part 2]
Shayan Fazeli
2.2 - Graph Representation Learning Book - Chapter 2 [Part 2]
21:54
2.1 - Graph Representation Learning Book - Chapter 2 [Part 1]
Shayan Fazeli
2.1 - Graph Representation Learning Book - Chapter 2 [Part 1]
13:29
1 - Graph Representation Learning Book - Chapter 1
Shayan Fazeli
1 - Graph Representation Learning Book - Chapter 1
20:44
2.4 - Graph Representation Learning Book - Chapter 2 [Part 4]
Shayan Fazeli
2.4 - Graph Representation Learning Book - Chapter 2 [Part 4]
23:15
3.1 - Graph Representation Learning Book - Chapter 3 [Part 1]
Shayan Fazeli
3.1 - Graph Representation Learning Book - Chapter 3 [Part 1]
29:04
3.2 - Graph Representation Learning Book - Chapter 3 [Part 2]
Shayan Fazeli
3.2 - Graph Representation Learning Book - Chapter 3 [Part 2]
26:40
3.3 - Graph Representation Learning Book - Chapter 3 [Part 3]
Shayan Fazeli
3.3 - Graph Representation Learning Book - Chapter 3 [Part 3]
34:39
3 - Graph Representation Learning Book - Chapter 3
Shayan Fazeli
3 - Graph Representation Learning Book - Chapter 3
26:40
4 - Graph Representation Learning Book - Chapter 4
Shayan Fazeli
4 - Graph Representation Learning Book - Chapter 4
29:04
5 - Graph Representation Learning Book - Chapter 5
Shayan Fazeli
5 - Graph Representation Learning Book - Chapter 5
1:01:18
6 - Graph Representation Learning Book - Chapter 6
Shayan Fazeli
6 - Graph Representation Learning Book - Chapter 6
10:30
7 - Graph Representation Learning Book - Chapter 7
Shayan Fazeli
7 - Graph Representation Learning Book - Chapter 7
1:25:41
8 - Graph Representation Learning Book - Chapter 8
Shayan Fazeli
8 - Graph Representation Learning Book - Chapter 8
8:53
9 - Graph Representation Learning Book - Chapter
Shayan Fazeli
9 - Graph Representation Learning Book - Chapter
30:05
PaperView - "Panoptic segmentation with a joint semantic and instance segmentation network"
Shayan Fazeli
PaperView - "Panoptic segmentation with a joint semantic and instance segmentation network"
8:19
PaperView: Generalized Wasserstein Dice Score for Imbalanced Segmentation
Shayan Fazeli
PaperView: Generalized Wasserstein Dice Score for Imbalanced Segmentation
29:11
PaperView: TabNN: A Universal Neural Network Solution for Tabular Data
Shayan Fazeli
PaperView: TabNN: A Universal Neural Network Solution for Tabular Data
24:18
PaperView: Transferable Adversarial Training - A General Approach to Adapting Deep Classifiers
Shayan Fazeli
PaperView: Transferable Adversarial Training - A General Approach to Adapting Deep Classifiers
31:26
Paper Explained: Complementary Relation Contrastive Distillation
Shayan Fazeli
Paper Explained: Complementary Relation Contrastive Distillation
30:43
Deep Patient
Shayan Fazeli
Deep Patient
13:36
Analyzing the Role of Model Uncertainty for Electronic Health Records
Shayan Fazeli
Analyzing the Role of Model Uncertainty for Electronic Health Records
24:05
Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer
Shayan Fazeli
Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer
18:26
Learning with Hypergraphs: Section 4
Shayan Fazeli
Learning with Hypergraphs: Section 4
6:42
Learning with Hypergraphs: Abstract
Shayan Fazeli
Learning with Hypergraphs: Abstract
1:58
Learning with Hypergraphs: Section 1
Shayan Fazeli
Learning with Hypergraphs: Section 1
2:07
Learning with Hypergraphs: Section 2
Shayan Fazeli
Learning with Hypergraphs: Section 2
7:21
Learning with Hypergraphs: Section 6
Shayan Fazeli
Learning with Hypergraphs: Section 6
2:36
Learning with Hypergraphs - Sections 3 and 5
Shayan Fazeli
Learning with Hypergraphs - Sections 3 and 5
18:41
Learning with Hypergraphs: Section 7
Shayan Fazeli
Learning with Hypergraphs: Section 7
1:00