|
48 | 48 | title: >
|
49 | 49 | <strong>Quiz</strong>
|
50 | 50 |
|
| 51 | +- title: "Module 2: Learning" |
51 | 52 |
|
| 53 | +- date: 2/18 |
| 54 | + lecturer: Prof. Lengerich |
| 55 | + title: > |
| 56 | + <strong>Learning Generalized Linear Models</strong> |
| 57 | +
|
| 58 | +- date: 2/20 |
| 59 | + lecturer: Prof. Lengerich |
| 60 | + title: > |
| 61 | + <strong>Parameter Learning in Fully-Observed BNs</strong> |
| 62 | +
|
| 63 | +- date: 2/25 |
| 64 | + lecturer: Prof. Lengerich |
| 65 | + title: > |
| 66 | + <strong>Learning Undirected GMs</strong> |
| 67 | +
|
| 68 | +- date: 2/27 |
| 69 | + lecturer: Prof. Lengerich |
| 70 | + title: > |
| 71 | + <strong>Structure Learning</strong> |
| 72 | +
|
| 73 | +- date: 3/4 |
| 74 | + lecturer: Prof. Lengerich |
| 75 | + title: > |
| 76 | + <strong>Causal Discovery</strong> |
| 77 | +
|
| 78 | +- date: 3/6 |
| 79 | + lecturer: Prof. Lengerich |
| 80 | + title: > |
| 81 | + <strong>Parameter Learning of partially observed BNs</strong> |
52 | 82 |
|
| 83 | +- date: 3/11 |
| 84 | + lecturer: Prof. Lengerich |
| 85 | + title: > |
| 86 | + <strong>Sequential Models</strong> |
| 87 | +
|
| 88 | + |
| 89 | +- date: 3/13 |
| 90 | + lecturer: Prof. Lengerich |
| 91 | + title: > |
| 92 | + <strong>Variational Inference, Monte Carlo</strong> |
| 93 | +
|
| 94 | +- date: 3/18 |
| 95 | + lecturer: Prof. Lengerich |
| 96 | + title: > |
| 97 | + <strong>Review</strong> |
| 98 | +
|
| 99 | +- date: 3/20 |
| 100 | + lecturer: Prof. Lengerich |
| 101 | + title: > |
| 102 | + <strong>Exam</strong> |
| 103 | +
|
| 104 | +- date: 3/25 |
| 105 | + lecturer: Prof. Lengerich |
| 106 | + title: > |
| 107 | + <strong>Spring recess</strong> |
| 108 | +
|
| 109 | +- date: 3/27 |
| 110 | + lecturer: Prof. Lengerich |
| 111 | + title: > |
| 112 | + <strong>Spring recess</strong> |
| 113 | +
|
| 114 | +
|
| 115 | +- date: 4/1 |
| 116 | + lecturer: Prof. Lengerich |
| 117 | + title: > |
| 118 | + <strong>Deep Learning from a GM Perspective</strong> |
| 119 | +
|
| 120 | +- date: 4/3 |
| 121 | + lecturer: Prof. Lengerich |
| 122 | + title: > |
| 123 | + <strong>CNNs, RNNs, Autoencoders</strong> |
| 124 | +
|
| 125 | +- date: 4/8 |
| 126 | + lecturer: |
| 127 | + title: > |
| 128 | + <strong>Deep Generative Models: GAN, VAEs</strong> |
| 129 | +
|
| 130 | +- date: 4/10 |
| 131 | + lecturer: Prof. Lengerich |
| 132 | + title: > |
| 133 | + <strong>Attention and Transformers</strong> |
| 134 | +
|
| 135 | +- date: 4/15 |
| 136 | + lecturer: Prof. Lengerich |
| 137 | + title: > |
| 138 | + <strong>LLMs from a Probabilistic Perspective 1: Implementing a GPT from Scratch</strong> |
| 139 | +
|
| 140 | +
|
| 141 | +- date: 4/17 |
| 142 | + lecturer: Prof. Lengerich |
| 143 | + title: > |
| 144 | + <strong>LLMs from a Probabilistic Perspective 2: Training on Unlabeled Data</strong> |
| 145 | +
|
| 146 | +
|
| 147 | +
|
| 148 | +- date: 4/22 |
| 149 | + lecturer: Prof. Lengerich |
| 150 | + title: > |
| 151 | + <strong>LLMs from a Probabilistic Perspective 3: Fine-tuning on Labeled Data</strong> |
| 152 | +
|
| 153 | + |
| 154 | +- date: 4/24 |
| 155 | + lecturer: Prof. Lengerich |
| 156 | + title: > |
| 157 | + <strong>Context-Adaptive Graphical Models</strong> |
| 158 | +
|
| 159 | +
|
| 160 | +- date: 4/29 |
| 161 | + lecturer: |
| 162 | + title: > |
| 163 | + <strong>Project Presentations</strong> |
| 164 | +
|
| 165 | +- date: 5/1 |
| 166 | + lecturer: |
| 167 | + title: > |
| 168 | + <strong>Project Presentations</strong> |
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